Compare multiple columns in 2 different dataframes in R

Question

I am trying to compare multiple columns in two different dataframes in R. This has been addressed previously on the forum ( Compare group of two columns and return index matches R ) but this is a different scenario: I am trying to compare if a column in dataframe 1 is between the range of 2 columns in dataframe 2 . Functions like match, merge, join, intersect won't work here. I have been trying to use purr::pluck but didn't get far. The dataframes are of different sizes.

Below is an example:

temp1.df <- mtcars

temp2.df <- data.frame(
  Cyl = sample (4:8, 100, replace = TRUE),
  Start = sample (1:22, 100, replace = TRUE),
  End = sample (1:22, 100, replace = TRUE)
)

temp1.df$cyl <- as.character(temp1.df$cyl)
temp2.df$Cyl <- as.character(temp2.df$Cyl)

My attempt:

temp1.df <- temp1.df %>% mutate (new_mpg = case_when (
  temp1.df$cyl %in% temp2.df$Cyl & temp2.df$Start <= temp1.df$mpg & temp2.df$End >= temp1.df$mpg ~ 1
))

Error:

Error in mutate_impl(.data, dots) : 
  Column `new_mpg` must be length 32 (the number of rows) or one, not 100

Expected Result:

1. Compare temp1.df$cyl and temp2.df$Cyl. If they are match then -->
2. Check if temp1.df$mpg is between temp2.df$Start and temp2.df$End -->
3. if it is, then create a new variable new_mpg with value of 1.

It's hard to show the exact expected output here.

I realize I could loop this so for each row of temp1.df but the original temp2.df has over 250,000 rows. An efficient solution would be much appreciated.

Thanks

Answer 1

temp1.df$new_mpg<-apply(temp1.df, 1, function(x) {
  temp<-temp2.df[temp2.df$Cyl==x[2],] 
  ifelse(any(apply(temp, 1, function(y) {
    dplyr::between(as.numeric(x[1]),as.numeric(y[2]),as.numeric(y[3]))
  })),1,0)
})

Note that this makes some assumptions about the organization of your actual data (in particular, I can't call on the column names within apply , so I'm using indexes - which may very well change, so you might want to rearrange your data between receiving it and calling apply , or maybe changing the organization of it within apply , eg, by apply(temp1.df[,c("mpg","cyl")]... .

At any rate, this breaks your data set into lines, and each line is compared to the a subset of the second dataset with the same Cyl count. Within this subset, it checks if any of the mpg for this line falls between (from dplyr ) Start and End , and returns 1 if yes (or 0 if no). All these ones and zeros are then returned as a (named) vector, which can be placed into temp1.df$new_mpg .

I'm guessing there's a way to do this with rowwise , but I could never get it to work properly...