Add new column based on coincidence of two columns - r

Question

I have these two starter data frames:
df1 <- data.frame("Location" = c('NE', 'SW', 'NW'), "Time" = c('0400', '1620', '2110'), "Assignment" = c('Painter', 'Astronaut', 'Bartender'), "Frequency" = c(84, 122, 139))
df1
Location Time Assignment Frequency
1 NE 0400 Painter 84
2 SW 1620 Astronaut 122
3 NW 2110 Bartender 139
df2 <- data.frame("Location" = c('NE', 'SW', 'NW', 'NW', 'SE'), "Time" = c('0400', '1620', '2110', '2240', '1410'), "Assignment" = c('Scripter', 'Port Patrol', 'Lawyer', 'Supplier', 'Youtuber'), "Frequency" = c(82, 126, 144, 94, 102))
df2
Location Time Assignment Frequency
1 NE 0400 Scripter 84
2 SW 1620 Port Patrol 122
3 NW 2110 Lawyer 139
4 NW 2240 Supplier 94
5 SE 1410 Youtuber 102
Suppose I didn't know which data frame was larger. But in this case, df2>df1 , so now I want to try and see which values of the columns 'Location' AND 'Time' coincide. For these equivalents, add a new column stating 'Coincide'. If not, this column should be NA.
For this, I tried:
df3$NewCol <- NA
df3$NewCol[df1$Location == df2$Location & df1$Time == df2$Time] <- 'Coincide'
or
if(df1$Location == df3$Location & df1$Time == df3$Time) {
df3$NewCol <- 'Coincide'
}
(In this ones I created a new df3 which is a merge of df1 + df2)
But on both of these tries I get the error:
longer object length is not a multiple of shorter object length
Which I believe is a problem on both data frames having different lengths, but how could I overcome this ?
Thanks in advance

Answer 1

Answering the first question of adding a new column with 'Coincide'.
We can do a full join with df1 and df2 which would give all the entries present in both the dataframes irrespective of their size. We can then check for NA values and assign 'Coincide' or NA value based on that.
all_data <- merge(df1, df2, by = c('Location', 'Time'), all = TRUE)
all_data$new_col <- c('Coincide', NA)[(rowSums(is.na(all_data[-c(1:2)])) > 0) + 1]
all_data
# Location Time Assignment.x Frequency.x Assignment.y Frequency.y new_col
#1 NE 0400 Painter 84 Scripter 82 Coincide
#2 NW 2110 Bartender 139 Lawyer 144 Coincide
#3 NW 2240 <NA> NA Supplier 94 <NA>
#4 SE 1410 <NA> NA Youtuber 102 <NA>
#5 SW 1620 Astronaut 122 Port Patrol 126 Coincide
You can then select only the columns that you need for further analysis.