Analysis of the Employment Situation in Costa Rica (2018-2022)

Overview

This project provides a detailed analysis of the employment trends in Costa Rica over the period from 2018 to 2022. The analysis aims to uncover significant patterns, changes, and key factors that have influenced the employment landscape in Costa Rica during these years. The study utilizes data from national surveys and statistical sources to present insights into various employment indicators.

Features

• Data Collection: Aggregation of employment data from reliable sources, covering various sectors and demographics in Costa Rica.
• Time-Series Analysis: Examination of employment trends over time, identifying periods of growth, stability, and decline.
• Sectoral Breakdown: Analysis of employment distribution across different economic sectors such as agriculture, industry, and services.
• Demographic Insights: Study of employment rates based on age, gender, education level, and geographical location.
• Policy Impact Assessment: Evaluation of the impact of government policies and economic conditions on employment trends.

Installation

1. Clone the repository:

   git clone https://github.com/Gaboelc/Analysis-of-the-employment-situation-in-Costa-Rica-2018-2022.git
   cd Analysis-of-the-employment-situation-in-Costa-Rica-2018-2022

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate

3. Install the required packages:

   pip install -r requirements.txt

Usage

1. Data Preparation: Load and preprocess the employment data using the data_preparation.ipynb notebook to ensure it's ready for analysis.

2. Exploratory Data Analysis (EDA): Use the EDA.ipynb notebook to explore the data, identify key trends, and visualize the employment situation across different years.

3. Time-Series Analysis: Run the time_series_analysis.ipynb notebook to perform detailed analysis on employment trends over time.

4. Sectoral and Demographic Analysis: Utilize the sectoral_demographic_analysis.ipynb notebook to break down employment data by sectors and demographics.

5. Reporting: Generate a comprehensive report using the report_generation.ipynb notebook, summarizing the findings of the analysis.

Datasets

The datasets used in this project are included in the data/ directory. These datasets comprise employment statistics sourced from Costa Rican national surveys, with details on various employment indicators.

Results

• The analysis revealed significant shifts in employment patterns, with notable changes in certain sectors and demographics.
• Detailed findings and visualizations are available in the corresponding Jupyter notebooks.

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Commit your changes (git commit -am 'Add new feature').
4. Push to the branch (git push origin feature-branch).
5. Create a new Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• The project is based on data provided by Costa Rican national statistical agencies and surveys.
• Special thanks to the open-source community for the tools and libraries used in this project.

Contact

For any questions or inquiries, please reach out via the repository's issue tracker.