This repository contains a data analysis project focused on analyzing Moroccan fish data. This project aims to conduct an analysis of the factors that influence the volume of coastal and artisanal fishing products in Morocco using Principal Component Analysis (PCA) with the R and Python programming languages.
The data used in this analysis has been extracted from the hcp.ma website and includes information on coastal and artisanal fishing in Morocco. The raw data can be found in the Dataset.xlsx file of this repository.
The main objective of this analysis is to determine the factors that have the most significant impact on the production of coastal fishing products in Morocco. We will seek to answer questions such as:
- What are the primary factors influencing the production of coastal fishing products in Morocco?
- Are there any interesting trends or correlations between different variables?
- How can this information be used to improve the management of coastal fishing in Morocco?
Principal Component Analysis (PCA) will be used to reduce the dimensionality of the data and identify the most significant factors. R and Python scripts will be used to perform this analysis.
Dataset.xlsx: The raw dataset downloaded from hcp.ma, containing information on coastal and artisanal fishing in Morocco.PCA.R: The R script used for Principal Component Analysis (PCA) to analyze the data.PCA.ipynb: The Jupyter Notebook containing the Python script for PCA and data analysis.Project Report.pdf: A PDF document summarizing the project's findings and conclusions.
