running paired wilcoxon test on rows of two dataframes

I have a two large dataframes (around 19000 rows and 71 columns) as follows
df1

df2

I am trying to perform wilcoxon rank sum test on the rows with the same index but the code is taking forever on google colab!!
My code so far

wilc_results= c()
for( x in 1:nrow(df1)){
  for (y in 1:nrow(df2)){
    result= wilcox.test(as.numeric(df2[y,]), as.numeric(f1d[x,]), 
                        alternative= 'two.sided', paired= T )
    wilc_results[length(wilc_results) + 1] <- result$p.value
  }
}

is there a much faster way to get the desired output?

>Solution :

There is no need to loop twice, since both your data frames have the same number of columns. It runs in about 10 seconds on a similarly sized dataset on my computer.

wilc_results <- list()
for(i in 1:nrow(df1)) {
  result <- wilcox.test(as.numeric(df1[i,]), as.numeric(df2[i,]),
                        alternative='two.sided', paired=T)
  wilc_results[[i]] <- result$p.value
}