apply a function with two dataframes as input in r - r

Question

I want to get the total number of NA that missmatch between two dataframes.
I have found the way to get this for two vectors as follows:
compareNA <- function(v1,v2) {
same <- (v1 == v2) | (is.na(v1) & is.na(v2))
same[is.na(same)] <- FALSE
n <- 0
for (i in 1:length(same))
if (same[i] == "FALSE"){
n <- n+1
}
return(n)
}
Lets say I have vector aand bwhen comparing them I got as a result 2
a <- c(1,2,NA, 4,5,6,NA,8)
b <- c(NA,2,NA, 4,NA,6,NA,8)
h <- compareNA(a,b)
h
[1] 2
My question is: how to apply this function for dataframes instead of vectors?
Having as an example this datafames:
a2 <- c(1,2,NA,NA,NA,6,NA,8)
b2 <- c(1,NA,NA,4,NA,6,NA,NA)
df1 <- data.frame(a,b)
df2 <- data.frame(a2,b2)
what i expect as a result is 5, since this are the total number of NAs that appear in df2 that are not in df1. Any suggestion how to make this work?

Answer 1

Here's a second thought.
xy1 <- data.frame(a = c(NA, 2, 3), b = rnorm(3))
xy2 <- data.frame(a = c(NA, 2, 4), b = rnorm(3))
com <- intersect(colnames(xy1), colnames(xy2))
sum(xy1[, com] == xy2[, com], na.rm = TRUE)
If you don't want to worry about column names (but you should), you can make sure the columns align perfectly. In that case, intersect step is redundant.
sum(xy1 == xy2, na.rm = TRUE)

Answer 2

A third way (assuming dimensions of df1 & df2 are same):
sum(sapply(1:ncol(df1), function(x) compareNA(df1[,x], df2[,x])))
# 5

Answer 3

It would be easier to force both dataframes to have the same column names and compare column by column when those have the same name. You can then simply use a loop over columns and increment a running total by applying your function.
compareNA.df <- function(df1, df2) {
total <- 0
common_columns <- intersect(colnames(df1), colnames(df2))
for (col in common_columns) {
total <- total + compareNA(df1[[col]], df2[[col]])
}
return(total)
}
colnames(df2) <- c("a", "b")
compareNA.df(df1, df2)