There are times when you need to merge multiple data frames in r and there are a couple of ways of performing this task. One is using the merge function and the other is combining the columns from the data frames into a single data frame using the data frame function. Each approach has different levels of flexibility and produces different results.
When you merge multiple data frames in r the merge function is one function you can use. The merge function is a base r designed for the merger of multiple data frames and it has the format of merge(x, y, by.x , by.y).
- x, y – Data frames to be merged.
- by.x, by.y – Specify the columns used.
Simple observation shows that problems can easily occur when there are mismatches in the data frames. The downside of using this function is the level of control that you have over the merger. You can produce a better merger that is easier to control and less error-prone by using the data frame function.
How To Use the Merge Function in R
The merge function supplies no means for merging row names and by default it uses the common column names in the merger. A row is produced by matching results from a different column in the data frames. The left join of each column forms the new data frame. The big problem with this function is that it does not do a complete merger of the data frames. Fortunately, this is not the only method for merging data frames. Done right, the data frame function can be used to merge multiple data frames with both ease and control. It requires more work, but the results are worth the effort.
Examples of Merging Multiple Columns in R
Here are two examples on how to merge multiple data frames. Each example uses a different method, and they produce different results.
> x = data.frame(a=c(1,2,3,4,5,6,7,8,9,10),
+ b=c(“A”,”G”,”R”,”H”,”S”,”C”,”F”,”Q”,”H”,”S”),
+ c=c(3,6,9,12,15,18,21,24,27,30),
+ d=c(4,8,12,16,20,24,28,32,36,40))
>
> y = data.frame(A=c(2,3,3,4,5,5,6,8,8,9),
+ B=c(1,2,3,4,5,6,7,8,9,10))
>
> z = data.frame(x=c(1,2,3,4,5,6,7,8,9,10),
+ y=c(0,1,0,0,0,1,1,1,1,1))
>
> merge(x, y, z, by.x = “a”, by.y = “A”)
a b c d B
1 2 G 6 8 1
2 3 R 9 12 2
3 3 R 9 12 3
4 4 H 12 16 4
5 5 S 15 20 5
6 5 S 15 20 6
7 6 C 18 24 7
8 8 Q 24 32 8
9 8 Q 24 32 9
10 9 H 27 36 10
In this example, we used the merge function, and it produces the results seen above. It actually only produces a merger of the first two data frames. It does not include anything uniques from the third one. If this is what you are looking for, then fine but otherwise you need to use a different method.
> x = data.frame(a=c(1,2,3,4,5,6,7,8,9,10),
+ b=c(“A”,”G”,”R”,”H”,”S”,”C”,”F”,”Q”,”H”,”S”),
+ c=c(3,6,9,12,15,18,21,24,27,30),
+ d=c(4,8,12,16,20,24,28,32,36,40))
>
> y = data.frame(A=c(2,3,3,4,5,5,6,8,8,9),
+ B=c(1,2,3,4,5,6,7,8,9,10))
>
>
> z = data.frame(x=c(1,2,3,4,5,6,7,8,9,10),
+ y=c(0,1,0,0,0,1,1,1,1,1))
>
> data.frame(a =x$a, b=x$b, c=x$c, d=x$d, A=y$A, B=y$B, x=z$x, y=z$y)
a b c d A B x y
1 1 A 3 4 2 1 1 0
2 2 G 6 8 3 2 2 1
3 3 R 9 12 3 3 3 0
4 4 H 12 16 4 4 4 0
5 5 S 15 20 5 5 5 0
6 6 C 18 24 5 6 6 1
7 7 F 21 28 6 7 7 1
8 8 Q 24 32 8 8 8 1
9 9 H 27 36 8 9 9 1
10 10 S 30 40 9 10 10 1
In this example, we use the data frame function to combine multiple columns from all three data frames into one object. In this case, we get all the columns, but if we wanted to, we could have reproduced the results of the first example.
Applications of Merging Multiple Columns in R
There are many situations where merging two or more data frames can come in handy. If you have two sets of related observations this process can easily produce a single data frame for the complete set. Using the data frame function, you can merge the entire contents into a single useful data set.
When you merge multiple data frames, there is more than one way of doing it. Each method produces different results and which one you use depends upon the situation. Once you learn and understand these techniques, you will find them more useful than you previously thought.