2025-11-02

The Dataset

-This project uses Dataset from Kaggle, which is regarding Life Expectancy. -The Dataset combines factors such as economic, social,and mainly health indicators to analyze what influences life Expectancy from many countries and years. -The Dataset has 22 columns, 2938 rows and it focuses on the factors affecting Life Expectancy across developing and developed nations.

Brief Overview

-This project explores Life Expectancy Dataset through different visualizations to better understand the factors that influence the average lifespan across countries and years. -It includes a world map to display average life expectancy by continent. -A scatter plot to show relationships between life expectancy and economic indicators like mortality and schooling. -A pie chart comparing developed and developing nations. -A box plot illustrating distribution across income groups, and a statistical analysis summarizing key measures like mean, median, and standard deviation.

##Ggplot World Map <Font size “2”) -This visualization shows the global variation in average life expectancy. The darker blue shades indicate countries with higher life expectancy,meaning that these countries have access to better healthcare. Lighter blue shades represent nations with lower life expectancy, meaning that economic influences on them and they have limited access to healthcare and yellow areas show missing or data that are not available. ## Plotly 3D plot: -The following is a 3D Scatter Plot of Life Expectancy in several factors.

3D plot Aanlysis:

-This above 3D animated plot shows the relationship between GDP per capita, schooling years and life expectancy across different continents from 2000 to 2015. -Each point shows a country, colored by continent, and the animation represents how these factors change over time. In short, the plot indicates that the nations with higher GDP and more years of schooling tend to have higher life expectancy which highlights a strong link between education, economic and mainly on health. ## Pie Chart

Analysis of pie chart:

-This pie chart shows the average life expectancy by continent. Europe has the highest share at 22%, indicating generally longer life spans compared to other regions. Africa has the lowest at 16.7%, reflecting lower life expectancy levels likely due to economic and health facilities. The Americas, Asia and Oceania each of them show 20-21%, showing relatively balanced averages.

Box Plot

-This box plot shows the distribution of life expectancy across continents.Europe has the highest median life expectancy with relatively low version. On the other hand, Africa has the lowest range, which shows that their health conditions is not satisfied enough. The Americas and Asia show moderate life expectancy levels. Finally, Oceania falls slightly below the Europe. ##Statistical Analysis:

## # A tibble: 5 × 8
##   continent  Mean    SD   Min    Q1 Median    Q3   Max
##   <chr>     <dbl> <dbl> <dbl> <dbl>  <dbl> <dbl> <dbl>
## 1 Africa     58.6  8.01  39    52.8   57.8  63.1    79
## 2 Americas   73.5  4.42  36.3  71.7   73.9  75.8    87
## 3 Asia       71.2  5.88  54.8  66.7   72.6  74.9    87
## 4 Europe     77.4  4.87  64.6  74.1   77.8  81      89
## 5 Oceania    71.2  6.38  58.9  67.5   69.4  73.6    89

-This statistical analysis summarizes average life expectancy across five continents. Europe shows the highest mean (77.43 years), followed closely by Asia and Oceania, while Africa has the lowest (58.61 years). The standard deviation values show greater variability in Africa. Quartile and median results reveal that developed regions generally have higher and more consistent life expectancies, whereas less developed areas like Africa and parts of the Americas show lower averages and wider variation.

Conclusion and thank you for your time!

-This project analyzes a Kaggle life expectancy dataset focusing on economic, social, and health indicators across countries. The analysis shows clear global patterns, developed regions like Europe and Oceania have higher and more consistent life expectancies, while Africa shows the lowest due to weaker economies and healthcare systems. Overall, the results highlight that higher GDP, better education, and stronger healthcare systems significantly contribute to increased life expectancy worldwide.