Correlate only columns with same name

Question

I have two huge dataframes with the same columns and row names but different values. Now i wanted to compute the correlation for each column between the two dataframes but only for the columns with the same name.

  yyyymm `10000` `10001` `10002` `10003` `10004` `10005` `10006`
   <int>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
1 198601      NA      NA      NA      NA      NA      NA      NA
2 198602      NA      NA      NA      NA      NA      NA      NA
3 198603      NA      NA      NA      NA      NA      NA      NA
4 198604      NA      NA      NA      NA      NA      NA      NA
5 198605      NA      NA      NA      NA      NA      NA      NA
6 198606      NA      NA      NA      NA      NA      NA      NA

both datframes look like this.

Meaning i want the correlation of the column 10001 of the first dataframe with 10001 of the second dataframe and so on.

PS: the missing values are only in the first rows.

Answer 1

Does this work:

set.seed(111)
df1 <- data.frame(c1 = rnorm(10),
                   c2 = rnorm(10),
                   c3 = rnorm(10))
 df2 <- data.frame(c1 = rnorm(10),
                  c3 = rnorm(10),
                  c2 = rnorm(10))
Map(cor, df1[sort(names(df1))], df2[sort(names(df2))])
$c1
[1] -0.02421313

$c2
[1] 0.2706937

$c3
[1] -0.1615181

OR:

unlist(Map(cor, df1[sort(names(df1))], df2[sort(names(df2))]))
         c1          c2          c3 
-0.02421313  0.27069371 -0.16151811 

Using purrr:

library(purrr)
pmap(list(df1[sort(names(df1))], df2[sort(names(df2))]), cor)
$c1
[1] -0.02421313

$c2
[1] 0.2706937

$c3
[1] -0.1615181