how to rank a correlation matrix?

I have found a correlation matrix for my data using the following code:

file_20 <- read.csv("C:/Desktop/ex.csv")
file_20
cor (file_20[,1:19], file_20[1:19], method ="spearman")

But now how can i rank my correlation matrix? Is there any suggestion

NOTE: I have 19 columns and 20 rows (including the header) and my aim is to rank the columns according to spearman rank correlation.

I tried doing

cor (rank(file_20[,1:19]), rank(file_20[1:19]), method ="spearman")

It showed output as

[1] 1

Is there any option to get all my columns of the table ranked?

Please help!

Solution

-- use the kendall method argument for cor() instead:

df <- data.frame(x=c(1,2,3,4,5), y=c(5,4,3,2,1))  
cor(df, method="kendall") 
   x  y 
x  1 -1    
y -1  1   
R> 
From help(cor):

For cor(), if method is "kendall" or "spearman", Kendall's tau or Spearman's rho statistic is used to estimate a rank-based measure of association. These are more robust and have been recommended if the data do not necessarily come from a bivariate normal distribution. For cov(), a non-Pearson method is unusual but available for the sake of completeness. Note that "spearman" basically computes cor(R(x), R(y)) (or cov(.,.)) where R(u) := rank(u, na.last="keep"). In the case of missing values, the ranks are calculated depending on the value of use, either based on complete observations, or based on pairwise completeness with reranking for each pair.