Merging two data.frames by key column

Question

I have two dataframes. In the first one, I have a KEY/ID column and two variables:

KEY V1 V2
1   10  2
2   20  4
3   30  6   
4   40  8
5   50 10

In the second dataframe, I have a KEY/ID column and a third variable

KEY V3 
1    5  
2   10  
3   20  

I would like to extract the rows of the first dataframe that are also in the second dataframe by matching them according to the KEY column. I would also like to add the V3 column to final dataset.

KEY V1 V2 V3 
1   10  2  5
2   20  4 10 
3   30  6 20   

This are my attempts by using the subset and the merge function

subset(data1, data1$KEY == data2$KEY) 
merge(data1, data2, by.x = "KEY", by.y = "KEY")

None of them does the task.

Any hint would be appreaciated. Thank you!

Answer 1

merge(data1, data2, by="KEY") should do it!

Answer 2

If what you want is an inner join, then your attempt should do it. If it doesn't check the formats of Key columns in both the table using class(data1$key).

Apart from these and the merge suggested by Christian, you can use -

library(plyr)
join(data1, data2, by="KEY", type="inner")

or

library(data.table)
setkey(data1, KEY)
setkey(data2, KEY)
data1[,list(data1,data2)]

Answer 3

You could use a dplyr *_join. Given the sample data, both of the following would give the same result:

library(dplyr)
df_merged <- inner_join(data1, data2, by = 'KEY')
df_merged <- right_join(data1, data2, by = 'KEY')

A inner_join returns all rows from df1 where there are matching values in df2, and all columns from df1 and df2.

A right_join returns all rows from df2, and all columns from df1 and df2.