An Analysis on the youth employment and unemployment sectors in Kenya and Rwanda
# Population and Education Analysis Dashboard
This repository contains code and data for analyzing population and education trends using Python, pandas, Plotly, and Streamlit.
## Link to Dashboard:
Youth - Employment/Unemployment in the IT Sector
## Table of Contents
1. Introduction
2. Getting Started
3. Installation
4. Data
5. Data Preprocessing
6. Population Analysis
7. Education Analysis
8. Running the Streamlit App
9. Insights
10. Contributing
11. License
## Introduction
This project aims to provide an interactive dashboard for analyzing population and education trends in different countries. The analysis is conducted using Python and its data visualization libraries, including pandas, Plotly, and Streamlit.
Getting Started
To use this code, follow the instructions below.
## Installation
Clone this repository to your local machine using:
```bash
git clone
github.com
```
Navigate to the repository directory:
```bash
cd Youth_Unemployment_IT
```
Create a virtual environment (optional but recommended):
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
Install the required packages:
```bash
pip install -r requirements.txt
```
## Data
The project utilizes two datasets:
ken_rwa_pop.csv: Population data with demographic information
ken_rwa_edu.csv: Education data with details on education levels and employment
## Data Preprocessing
The datasets are preprocessed to handle missing values and ensure data consistency.
## Population Analysis
The population analysis includes the following visualizations:
Total inactive population by year and sex
Total unemployed population by sex
Total employed population by year and sex
IT employment trends by year and gender
## Education Analysis
The education analysis includes the following visualizations:
Education level distribution by age group
Total unemployed population by education level and year
Total employed population by e …