merge in R results in more rows than one of the data frames

Question

I have two data frames, the first contains 9994 rows and the second contains 60431 rows. I want to merge the two data frames such that the merged data frame contains combined columns of both data frames but only contains 9994 rows.

However, I get more than 9994 rows upon merge. How can I make sure this does not happen?

df1 = readRDS('data1.RDS')
nrow(df1)
# [1] 9994

df2 = readRDS('data2.RDS')
nrow(df2)
# [1] 60431

df = merge(df1,df2,by=c("col1","col2"))
nrow(df)
# [1] 10057

df = merge(df1,df2,by=c("col1","col2"),all.x=TRUE)
nrow(df)
# [1] 10057
nrow(na.omit(df))
# [1] 10057

EDIT : Following akrun's comment. Yes, there were duplicates in the second data frame

nrow(unique(df2[,c("col1","col2")]))
# [1] 60263
nrow(df2)
# [1] 60431

How can I take only one row from a data frame if there are multiple for the same {col1,col2} combination. When I merge, I would like to have only 9994 rows.

Answer 1

This should work, be sure to sort df2 first so you select the right rows.

df = merge(
  df1,
  df2[!duplicated(df2[, c("col1","col2")], ],
  by=c("col1","col2"),
  all.x=TRUE
)

What happens here: I merge the two data frames by the columns we want to merge by, but I first select only the first occurrence of any combination of col1 and col2 from the second data.frame df2.

duplicated checks if lines are duplicated if called with a data.frame. I select col1 and col2 from df2, so duplicated returns TRUE for rows with the same col1 and col2 but differences in other cols. Then I select only the rows which are not duplicated.

(Read the [-expressions carefully, and check the function calls from the inside out, to get the intermediate results)

edit: added explanation as suggested in comments