Is there an R function for calculating Spearman correlation coefficient for each row in df and writing it as a vector?

Question

I am wondering whether there is an R function or package for calculating Spearman correlation coefficient for each row in df and writing it as a vector?

Reproducible example first:

deviation <- c(5.712840e-03, 5.712840e-02, 5.712840e-01, 5.712940e-01,5.712840e-06)
number <- c(45, 60, 16, 70, 19)
df  <- data.frame(deviation, number)

My df have 5 rows and 2 columns. I wanted to calculate Spearman correlation for each row, so that later I can add one more column with 5 rho's to my df. I understood there was a function cor.test that calculates the correlation coefficients. However, it doesn't help me to solve my task because I will get only one coefficient after it like

test <- cor.test(deviation, number, method="spearman")
test

It will give only one rho.

Could anyone, please, recommend me some package or function in R that can help to solve this task.

Answer 1

In addition to the comment of Ben Bolker I guess you are looking for something like this:

cor.test(df$deviation, df$number, method = "spearman")  

gives

    Spearman's rank correlation rho

data:  df$deviation and df$number
S = 12, p-value = 0.5167
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho 
0.4 

In order to put the estimates in a data frame you can use tidy() from broom package:

library(broom)
cor.test(df$deviation, df$number, method = "spearman") %>% tidy()

gives:

# A tibble: 1 x 5
  estimate statistic p.value method                          alternative
     <dbl>     <dbl>   <dbl> <chr>                           <chr>      
1      0.4        12   0.517 Spearman's rank correlation rho two.sided  

You then can make a function and use it:

cor_fun <- function(df) cor.test(df$deviation, df$number, method = "spearman") %>% tidy()
cor_fun(df)