The Spearman coefficient can be calculatated only for two characteristics of the observed population, as for kendall's W there may be two or more characteristics.
Spearman's rank correlation coefficient
Karl Pearson's coefficient, also known as Pearson's correlation coefficient, measures the linear relationship between two continuous variables and assumes that the data is normally distributed. In contrast, Spearman's rank-order coefficient assesses the strength and direction of the relationship between two ranked variables, making it suitable for non-parametric data or ordinal data. While Pearson's coefficient evaluates the actual values, Spearman's focuses on the ranks, allowing it to capture monotonic relationships even when they are not linear.
spearman rhos
Data ranks come from sorting the data. Manually ordering large sets of data can be time consuming, but very easy with spreadsheet programs. There are alternative means of calculating correlation, but if you are to use Spearman's rank correlation, you have to order each data set and determine ranks.
Spearman's rank correlation coefficient is given in the related link at the bottom of this page.
Spearman's rank correlation coefficient
Although Spearman's rank correlation coefficient puts a numerical value between the linear association between two variables, it can only be used for data that has not been grouped.
I would use Spearman and Kendall
http://ten.com.au/the-spearman-experiment.htm
Alexander Spearman was born in 1901.
Alexander Spearman died in 1982.
Craig Spearman was born in 1972.
Glenn Spearman was born in 1947.
Glenn Spearman died in 1998.
Robert Spearman died in 1761.
Robert Spearman was born in 1703.