Press "Enter" to skip to content

How to merge objects in R?

Zigya Acadmey 0

In this article, you’ll learn how to merge objects in R. Merging objects is a very frequently used concept in data analysis. R provides a broad range of capabilities to deal with merging data which are quite fundamental to R programming.

Merge two data frames by common columns or row names.

Usage

> merge(x, y, by, by.x, by.y, sort = TRUE)

Arguments

ValueDescription
x, ydata frames or objects to be coerced to one.
by, by.x, by.yspecifications of the common columns. See Details.
sortlogical. Should the results be sorted on the by columns?

By default, the data frames are merged on the columns with names they both have, but separate specifcations of the columns can be given by by.x and by.y. Columns can be specified by name, number or by a logical vector: the name "row.names" or the number 0 specifies the row names. The rows in the two data frames that match on the specified columns are extracted, and joined together. If there is more than one match, all possible matches contribute one row each.

If the remaining columns in the data frames have any common names, these have ".x" and ".y" appended to make the names of the result unique.

Adding Columns

To merge two data frames (datasets) horizontally, use the merge function. In most cases, you join two data frames by one or more common key variables (i.e., an inner join).

> df1 <- data.frame(x = month.abb, y = 1:12, z = letters[1:12])
> df1
     x  y z
1  Jan  1 a
2  Feb  2 b
3  Mar  3 c
4  Apr  4 d
5  May  5 e
6  Jun  6 f
7  Jul  7 g
8  Aug  8 h
9  Sep  9 i
10 Oct 10 j
11 Nov 11 k
12 Dec 12 l

> df2 <- data.frame(x = month.abb, a = 101:112, b = LETTERS[1:12])
> df2
     x   a b
1  Jan 101 A
2  Feb 102 B
3  Mar 103 C
4  Apr 104 D
5  May 105 E
6  Jun 106 F
7  Jul 107 G
8  Aug 108 H
9  Sep 109 I
10 Oct 110 J
11 Nov 111 K
12 Dec 112 L

Now, merging df1 and df2 data frames by column name ‘x’.

> DF <- merge(df1,df2,by='x')
> DF
     x  y z   a b
1  Apr  4 d 104 D
2  Aug  8 h 108 H
3  Dec 12 l 112 L
4  Feb  2 b 102 B
5  Jan  1 a 101 A
6  Jul  7 g 107 G
7  Jun  6 f 106 F
8  Mar  3 c 103 C
9  May  5 e 105 E
10 Nov 11 k 111 K
11 Oct 10 j 110 J
12 Sep  9 i 109 I

Combine two Objects by Columns or Rows

Combine two “matrix-like” R objects by columns (cbind) or rows (rbind).

Usage

> cbind(x, y)
> rbind(x, y)

Arguments

ValuesDescription
xany R object, typically “matrix-like”.
yany R object, typically similar to x, or missing completely.

Adding datasets vertically

To join two data frames (datasets) vertically, use the rbind() function. The two data frames must have the same variables, but they do not have to be in the same order.

> df1 <- data.frame(x=letters[1:10], y=c(1:10))
> df1
   x  y
1  a  1
2  b  2
3  c  3
4  d  4
5  e  5
6  f  6
7  g  7
8  h  8
9  i  9
10 j 10

> df2 <- data.frame(x=letters[11:20], y=c(11:20))
> df2
   x  y
1  k 11
2  l 12
3  m 13
4  n 14
5  o 15
6  p 16
7  q 17
8  r 18
9  s 19
10 t 20

Now, applying rbind() function to add the rows of df1 and df2 data frame.

> DF <- rbind(df1, df2)
> DF
   x  y
1  a  1
2  b  2
3  c  3
4  d  4
5  e  5
6  f  6
7  g  7
8  h  8
9  i  9
10 j 10
11 k 11
12 l 12
13 m 13
14 n 14
15 o 15
16 p 16
17 q 17
18 r 18
19 s 19
20 t 20

Adding datasets horizontally

To join two data frames (datasets) horizontally, use the cbind() function. The two data frames must have the same number of rows, but they do not have to be in the same order nor save type.

# First data frame
> model <- data.frame(Make=c("Audi", "Ford", "BMW"), "No.of Model"=c(17, 12, 20))
> model
  Make No.of.Model
1 Audi          17
2 Ford          12
3  BMW          20

# Second data frame
> sales <- data.frame(Make=c("Audi", "Ford", "BMW"), Sales=c(32123, 24124, 12342))
> sales
  Make Sales
1 Audi 32123
2 Ford 24124
3  BMW 12342

Now, let’s add columns from both the data frames using cbind() function

> cbind(model, sales)
  make No.of.Model Make Sales
1 Audi          17 Audi 32123
2 Ford          12 Ford 24124
3  BMW          20  BMW 12342

Conclusion

Hence, we saw how to merge to object in R, and also saw the rbind() and cbind() function and how to use them.

This brings the end of this Blog. We really appreciate your time.

Hope you liked it.

Do visit our page www.zigya.com/blog for more informative blogs on Data Science

Keep Reading! Cheers!

Zigya Academy
BEING RELEVANT

Leave a Reply

Your email address will not be published.