18

I have 2 data frames w/ 5 columns and 100 rows each. 

id       price1      price2     price3     price4     price5
 1         11.22      25.33      66.47      53.76      77.42
 2         33.56      33.77      44.77      34.55      57.42
...

I would like to get the correlation of the corresponding rows, basically 

for(i in 1:100){    
cor(df1[i, 1:5], df2[i, 1:5])    
}

but without using a for-loop. I'm assuming there's someway to use plyr to do it but can't seem to get it right. Any suggestions?

zx8754
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screechOwl
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2 Answers2

28

Depending on whether you want a cool or fast solution you can use either

diag(cor(t(df1), t(df2)))

which is cool but wasteful (because it actually computes correlations between all rows which you don't really need so they will be discarded) or

A <- as.matrix(df1)
B <- as.matrix(df2)
sapply(seq.int(dim(A)[1]), function(i) cor(A[i,], B[i,]))

which does only what you want but is a bit more to type.

Simon Urbanek
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    +1 That first one is cool. Also, `t(as.matrix(df1))` can become `t(df1)`, etc., since the coercion to matrix takes place implicitly when `t()` is passed a data.frame. – Josh O'Brien Feb 03 '12 at 22:22
  • Ah, great, thanks (this is where my low-level thinking gets me ;)), I'll edit that – Simon Urbanek Feb 03 '12 at 22:51
8

I found that as.matrix is not required.

Correlations of all pairs of rows between dataframes df1 and df2:

sapply(1:nrow(df1), function(i) cor(df1[i,], df2[i,]))

and columns:

sapply(1:ncol(df1), function(i) cor(df1[,i], df2[,i]))
Kamil Slowikowski
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  • can I use the same here in m case I want to find the correlation between gene expression and methylation where my gene sets are same for both the data sets or data frame ? – PesKchan Oct 10 '22 at 09:58