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Rbind In R

Last Updated : 17 Apr, 2024
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In this article, we will discuss what is Rbind function and how it works in the R Programming Language.

What is the Rbind function in R?

rbind() is a function in R used to combine multiple data frames or matrices by row-binding them together. This function appends the rows of the second (and subsequent) data frame(s) or matrix/matrices to the first data frame or matrix.

rbind(..., deparse.level = 1)
  • …: Represents the data frames or matrices to be combined. You can provide multiple arguments separated by commas.
  • deparse.level: Controls the level of deparsing to be done.

Let’s say you have two data frames df1 and df2, and you want to combine them row-wise using rbind():

R
# Create sample data frames
df1 <- data.frame(ID = 1:3, Name = c("Jack", "Albert", "Boby"))
df2 <- data.frame(ID = 4:6, Name = c("Emma", "Michael", "Sophia"))
df1
df2
# Combine data frames using rbind
combined_df <- rbind(df1, df2)
# Print the combined data frame
print(combined_df)

Output:

 df1
  ID   Name
1 1 Jack
2 2 Albert
3 3 Boby df2 ID Name 1 4 Emma 2 5 Michael 3 6 Sophia Print the combined data frame ID Name
1 1 Jack
2 2 Albert
3 3 Boby 4 4 Emma 5 5 Michael 6 6 Sophia

In this example, rbind() combines the rows of df1 and df2, resulting in a new data frame combined_df with all the rows from both df1 and df2.

You can also use rbind() to combine matrices in a similar way:

R
# Create sample matrices
mat1 <- matrix(1:6, nrow = 2)
mat2 <- matrix(7:12, nrow = 2)
mat1
mat2
# Combine matrices using rbind
combined_mat <- rbind(mat1, mat2)
# Print the combined matrix
print(combined_mat)

Output:

mat1    
 [,1] [,2] [,3]
[1,]    1    3    5
[2,]    2    4    6

mat2
     [,1] [,2] [,3]
[1,]    7    9   11
[2,]    8   10   12

Print the combined matrix
     [,1] [,2] [,3]
[1,]    1    3    5
[2,]    2    4    6
[3,]    7    9   11
[4,]    8   10   12

Here, rbind() combines the rows of mat1 and mat2, resulting in a new matrix combined_mat with all the rows from both matrices.

Conclusion

rbind() is particularly useful when you need to combine data frames or matrices that have the same column names or dimensions, respectively.


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