Correlation Matrix

data= read.csv(file.choose())

library(corrplot)

library(RColorBrewer)

library(psych)

data<-cbind(X,Y)

corMat = cor(data, method="spearman")

cor.plot(corMat,numbers=TRUE,colors=TRUE,tl.col="black", tl.srt=45,

         n=51,main=NULL,labels=NULL,

         cex =1.1,

         cex.lab = 0.8,

         cex.axis =0.8, #right side level

         cex.main = 0.8,

         cex.sub = 0.8)

Alternate way

###

corMat = cor(data, method="spearman")

col <- colorRampPalette(c("#BB4444", "#EE9988", "#FFFFFF", "#77AADD", "#4477AA"))

corrplot(corMat, method="color", col=col(200),  

         type="upper", order="hclust", 

         addCoef.col = "black", # Add coefficient of correlation

         tl.col="black", tl.srt=65, #Text label color and rotation

         # hide correlation coefficient on the principal diagonal

         diag=FALSE 

)