Life Expectancy Analysis Project by Gurkirat BainsLife Expectancy Analysis Project by Gurkirat Bains

Life Expectancy Analysis Project

Gurkirat Bains

Data Analyst

pandas

Python

scikit-learn

Data

Life-expectancy-analysis-project

Project Overview

This project focuses on analyzing Life Expectancy data to understand the key factors that influence how long people live across different countries and years. Using Python and data science techniques, the project performs data cleaning, exploratory data analysis (EDA), feature understanding, and insights generation.

The goal is to:

Explore global life expectancy trends

Identify important socio-economic and health-related factors

Practice real-world data analysis using Python

This project is suitable for Data Analyst / Data Science portfolio demonstration.

Project Structure

Life-Expectancy-Project/
│── life_expectancy_improved.ipynb   # Main Jupyter Notebook
│── Life Expectancy Data.csv         # Dataset used in the project
│── README.md                        # Project documentation

Dataset Information

Dataset Name: Life Expectancy Data

Format: CSV

Rows: Multiple country-year observations

Key Features Include:

Country

Year

Life expectancy

Adult Mortality

GDP

Schooling

Alcohol consumption

BMI

Health expenditure

The dataset contains missing values and real-world inconsistencies, making it ideal for practical data analysis.

Tools & Technologies Used

Programming Language: Python

Environment: Jupyter Notebook

Libraries:

pandas – data manipulation

numpy – numerical operations

matplotlib & seaborn – data visualization

scikit-learn – preprocessing and analysis

Project Workflow

1️ Data Loading

Imported the dataset using pandas

Inspected shape, columns, and data types

2️ Data Cleaning

Handled missing values

Removed or corrected inconsistent data

Converted data types where necessary

3️ Exploratory Data Analysis (EDA)

Analyzed life expectancy trends over years

Compared developed vs developing countries

Studied correlations between life expectancy and key factors

Visualized distributions and relationships using plots

4️ Insights & Observations

Higher schooling and GDP are strongly associated with higher life expectancy

Adult mortality shows a strong negative correlation

Developed countries generally have higher and more stable life expectancy trends

Key Visualizations

Life expectancy trends over time

Correlation heatmaps

Distribution plots of major variables

Country-wise comparisons

Future Improvements

Build a machine learning model to predict life expectancy

Perform feature importance analysis

Add interactive dashboards (Power BI / Tableau)

Apply advanced statistical analysis

Author

Gurkirat Bains Aspiring Data Scientist

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Posted Feb 25, 2026

This project focuses on analyzing Life Expectancy data to understand the key factors that influence how long people live across different countries and years

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