James-Muguro/UnemploymentTrendsEA

This repository contains datasets, code, and analyses focusing on unemployment trends in East Africa. Data is sourced from the International Labour Organization (ILO) and the World Bank. The repository aims to provide insights into unemployment dynamics in the region to support research and policymaking efforts. # Unemployment Trends in East Africa Analysis This project aims to analyze and forecast unemployment trends in East African countries using historical data sourced from the International Labour Organization (ILO) and the World Bank. The analysis includes data preprocessing, exploratory data analysis (EDA), predictive modeling, and visualization to provide insights into unemployment rates and forecast future trends. ## Installation To run the analysis code, you need to have Python installed on your system along with the following libraries: ```bash pip install pandas matplotlib seaborn scikit-learn numpy ``` ## Data Sources The dataset used for this analysis is sourced from the World Bank's World Development Indicators, specifically focusing on the unemployment indicator provided by the International Labour Organization (ILO). You can access the data from the following link: World Bank - Unemployment Indicator ## Analysis Steps 1. **Data Cleaning and Preprocessing**: The dataset undergoes cleaning and preprocessing to handle missing values, outliers, and format the data for analysis. 2. **Exploratory Data Analysis (EDA)**: Various EDA techniques are employed to understand the distribution, trends, and relationships within the data. This includes visualizations such as line plots, histograms, and correlation matrices to uncover patterns and insights. 3. **Predictive Modeling**: A predictive model is built using machine learning algorithms to forecast future unemployment rates for East African countries. Linear regression is used as a simple model to demonstrate the forecasting process. 4. **Data Visualization**: Visualizations are created to effectively communicate insights from the analysis, including trends in unemployment rates over time, comparisons between countries, and forecasted trends for the future. ## Results The analysis provides valuable insights into unemployment trends in East African countries, highlighting patterns, relationships, and for …