问题
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!
回答1:
merge(data1, data2, by="KEY") should do it!
回答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)]
回答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.
来源：https://stackoverflow.com/questions/23560789/merging-two-data-frames-by-key-column