CA in Practice is a project aimed at replicating and implementing the examples of Correspondence Analysis (CA) as presented in Michael Greenacre's book "La práctica del análisis de correspondencias" (Fundación BBVA, 2008), which is the Spanish edition of the second edition of "Correspondence Analysis in Practice". The focus of this project is to provide a practical, hands-on replication of the exercises and methods demonstrated in the book, offering users an accessible and functional implementation in Python.
The project’s goal is to faithfully reproduce the results from the original examples in Greenacre's book. The datasets used in this project are obtained from the CARME-N network, which serves as a repository for correspondence analysis data and related methods.
The main objectives of this project are:
- To apply the principles of Correspondence Analysis (CA) through the practical implementation of examples.
- To replicate exercises from "La práctica del análisis de correspondencias", the Spanish edition of the second edition of "Correspondence Analysis in Practice" by Michael Greenacre.
- To verify and validate the outcomes of these exercises by comparing them with those presented in the book.
- To adapt the original code from R to Python, allowing for broader accessibility to the examples and methods.
The repository is organized as follows:
- notebooks/: Jupyter notebooks replicating the exercises and concepts from Greenacre's book.
- Each notebook corresponds to a chapter or a specific topic from the book.
The datasets required to run the notebooks are not included in the repository but can be downloaded from the CARME-N network at CARME-N datasets.
This project is inspired by and based on the book "La práctica del análisis de correspondencias" by Michael Greenacre (Fundación BBVA, 2008). The implementation of the concepts and exercises presented in this repository is intended solely for educational purposes.
The original code examples from the book were written in R. These have been adapted to Python in this project, making the analyses more accessible to a wider audience. All adaptations have been carefully reviewed to match the original results as presented by Greenacre.
The datasets used in this project are sourced from the CARME-N network, which can be found at CARME-N Official Website.
Michael Greenacre has not participated in, approved, or endorsed this work. The concepts and methodologies implemented here are interpreted and applied independently by the project author, L. Felipe Castañeda G., based on the knowledge presented in Greenacre's book. Any errors or modifications from the original work are solely the responsibility of the author of this repository.
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Clone the repository:
git clone https://github.com/lfelipecas/ca-in-practice.git -
Navigate to the
notebooks/directory to explore the Jupyter notebooks, which provide detailed step-by-step replications of the analyses from the book. -
The datasets needed for each notebook are stored in the
data/directory. These datasets are sourced from the CARME-N datasets and loaded directly into each notebook.
This project uses Python 3.9.19. The required Python libraries are included in the requirements.txt file:
numpypandasmatplotlibseabornprincescipyjupyterlab
To install the dependencies, run:
pip install -r requirements.txt
The CARME-N network offers valuable resources for correspondence analysis and related methods. The datasets and some of the original R code used in this project are sourced from CARME-N. For more information and resources, visit the CARME-N website.
This project was created by L. Felipe Castañeda G.. Feel free to connect with me:
- GitHub: https://github.com/lfelipecas
- LinkedIn: https://www.linkedin.com/in/l-felipe-casta%C3%B1eda-g-008027155/
Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
You are free to:
- Share — copy and redistribute the material in any medium or format.
- Adapt — remix, transform, and build upon the material.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
For more details, refer to: CC BY-NC 4.0 License.
- Greenacre, Michael. "La práctica del análisis de correspondencias". Fundación BBVA, 2008.
- CARME-N: Correspondence Analysis and Related Methods