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https://github.com/gaboelc/analysis-of-the-employment-situation-in-costa-rica-2018-2022
This is an analysis with data extracted from the INEC in order to identify the changes that occurred in the Costa Rican labor market before, during and after the COVID-19 pandemic.
https://github.com/gaboelc/analysis-of-the-employment-situation-in-costa-rica-2018-2022
costa-rica data-analysis empleo employment
Last synced: about 1 month ago
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This is an analysis with data extracted from the INEC in order to identify the changes that occurred in the Costa Rican labor market before, during and after the COVID-19 pandemic.
- Host: GitHub
- URL: https://github.com/gaboelc/analysis-of-the-employment-situation-in-costa-rica-2018-2022
- Owner: Gaboelc
- License: mit
- Created: 2022-08-13T10:51:41.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-19T10:21:50.000Z (5 months ago)
- Last Synced: 2024-08-19T12:18:54.439Z (5 months ago)
- Topics: costa-rica, data-analysis, empleo, employment
- Language: Jupyter Notebook
- Homepage:
- Size: 905 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 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:
```bash
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:
```bash
python3 -m venv venv
source venv/bin/activate
```
3. Install the required packages:
```bash
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](https://www.inec.cr/), 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](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.