You will need to provide more information, preferably a reprex, to provide any help.
In general, if you want to get a correlation matrix, it is really simple using the cor function.
# setting seed
set.seed(seed = 23493)
# generating random data
x1 <- runif(n = 100)
x2 <- rnorm(n = 100)
x3 <- rcauchy(n = 100)
x4 <- rexp(n = 100)
x5 <- rlogis(n = 100)
# combining to get a dataset of 5 columns
d <- data.frame(x1,
x2,
x3,
x4,
x5)
# finding correlation matrix
(r <- cor(x = d))
#> x1 x2 x3 x4 x5
#> x1 1.000000000 0.005969777 0.04610351 0.080191762 -0.090464853
#> x2 0.005969777 1.000000000 0.14000817 -0.027236185 -0.094456667
#> x3 0.046103509 0.140008173 1.00000000 0.056563325 -0.080159816
#> x4 0.080191762 -0.027236185 0.05656333 1.000000000 -0.008438071
#> x5 -0.090464853 -0.094456667 -0.08015982 -0.008438071 1.000000000
Created on 2019-02-10 by the reprex package (v0.2.1)