This aim of this project is to perform exploratory data analysis on life expectancy and adult mortality from 2004 to 2014 in the regions of Asia, Africa, Europe, North America, Central America, South America and the Caribbean.
The below research questions were aimed at being answered:
- How life expectancy and mortality was affected by the following parameters: Population BMI(body mass index) Alcohol consumption Education GDP (Gross domestic product)
- How do these parameters change in the given countries
- What is the correlation between them?
- What may possibly affects them changing?
- Can any trend be observed? If so what is the trend?
The dataset was taken from Kaggle (https://www.kaggle.com/datasets/arunjangir245/life-expectancy-data). In order to answer the research questions, the project was divided into four parts. Part 1 looks at doing a comparison of GDP against life expectancy, including population across the entire dataset. Part 2 is about statistical summary on GDP (mean, max and min) per country within each region. Part 3 focuses on the regions Africa and Asia. Here the disease data are compared and correlated with life expectancy. Part 4 zooms in on the life expectancy in the American regions, looking at means, max, min and distribution and change within each country and per region.
Once the dataset is downloaded, a few steps need to be taken to prepare if for the analysis. Firstly, there are a lot of spaces in the titles which should be removed. Also, a column with the different regions should be added for the entire dataset. To aid anaylsis, the dataset was split for each part per region or factors which were being analysed. All the analysis was performed in Jupyter Notebook.
This project is a collaboration between Gwendoline Grenu, Temitope Ajose-Adeogun, Peter Lehel and Farheen Oomatia.
Along with the dataset from Kaggle, we used the following sources to aid us in performin the analysis and written writeup of the results
- Stack Overflow
- Google search