Exploratory factor analysis (EFA) is a method that aims to uncover structures in large variable sets. If you have a data set with many variables, it is possible that some of them are interrelated, i.e. correlate with each other. These correlations are the basis of factor analysis.
The aim of the factor analysis is to divide the variables into groups. The aim is to separate those variables that correlate highly from those that correlate less strongly.
In Statistics Exploratory Factor Analysis is also called Principal Component Analysis (PCA)
More Information about Exploratory Factor Analysis
https://datatab.net/tutorial/exploratory-factor-analysis
Here you can find the Factor Analysis Calculator
https://datatab.net/statistics-calculator/factor-analysis
And the Data:
https://datatab.net/assets/examples/PCA_Example.xlsx