May I add supplementary materials and an often omitted point that the correlation matrix is useful only when the data (of 2+ variables) is ‘normally distributed’ – like many other ‘common’ statistical tests. Thus before we go into correlation matrix we have to assure that ‘normal distribution’ is tested.

A guide to appropriate use of Correlation coefficient in medical Research https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3576830/
–In summary, correlation coefficients are used to assess the strength and direction of the linear relationships between pairs of variables. When both variables are normally distributed use Pearson’s correlation coefficient, otherwise use Spearman’s correlation coefficient.

Chapter 22: Correlation Types and When to Use Them https://ademos.people.uic.edu/Chapter22.html
Should I use Pearson or Spearman or Kendall? [Emphasis: Assuption 4]–We can see Pearson and Spearman are roughly the same, but Kendall is very much different. That’s because Kendall is a test of strength of dependency (i.e. one could be written as a linear function of the other), whereas Pearson and Spearman are nearly equivalent in the way they correlate ‘normally distributed ‘ data.