# 🌍 Job-lens - An African employment trend and forecasting platform.
## Project Description
Job-lens is a data-driven solution developed to analyze historical employment trends across African countries and forecast future employment patterns .
The platform transforms labour market data into interactive visualizations and predictive insights to support evidence-based decision-making for policymakers, researchers, investors, and job seekers.
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# Dataset
**Dataset Name:** ILOSTAT Employment by Economic Activity Dataset
**Source:** Hugging Face
**Dataset Size:**
| Metric | Value |
|--------|------:|
| Records | 39,600+ |
| Countries | Multiple African Countries |
| Time Period | Multiple Years |
| Variables | Employment, Economic Activity, Gender, Employment Type, Country, Year |
**Key Features**
- Country
- Year
- Economic Activity (ISIC Rev.4)
- Employment Type (Formal / Informal)
- Gender
- Number of Employees (Thousands)
- Data Quality Indicators
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# Exploratory Data Analysis:
* Service provisions have employed the highest number of people
* Under the minor sector, agriculture individually has the highest number of employees.
* Over time, service provision has been generally employing a higher workforce gradually.
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# Tech Stack
- Python 3
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Plotly
- Scikit-LLearn
- Prophet
- Streamlit
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# How to Run
1. Clone the repository.
```bash
git clone
github.com
```
2. Navigate into the project folder.
```bash
cd labourlens
```
3. Install the required packages.
```bash
pip install -r requirements.txt
```
4. Launch the Streamlit application.
```bash
streamlit run app.py
```
5. Explore employment trends, interactive dashboards, and employment forecasts across African countries.
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# Key Findings
- Services and agriculture account for the largest share of employment across many African economies.
- Informal employment is the more significantly rising employment secto …