In this article, we are going to see how to insert multiple rows in the dataframe in R Programming Language. First, let's create a DataFrame

To create a data frame we need to use vectors. We need to create vectors with some values and pass the vectors into data.frame() function as parameter. Thus, a data frame is created. Let us see an example that demonstrates the above statement.

Example 1:

# here num and branches are the vectors, ans those
# are passed into data.frame() as parameters .
dataframe = data.frame(num=c(1:3),branches=c("IT","CSE","ECE"))

# In this example we created vectors inside the
# data frame() function and assigned values to vectors. 
print(dataframe)

 
Output: 

In the above example, we have created a data frame with vectors directly as parameters. We can create data frames with already created vectors. Let us see an example.

Steps to insert multiple rows into a data frame

1. Create a dataframe.
2. Create a vector that contains rows to be added to the dataframe.
3. Use the below method to add rows to the data frame.

Implementation :

The predefined function used to add multiple rows is rbind(). We have to pass a data frame and a vector having rows of data. So, let see the example code. 

Indexing for a dataframe in R: 

variable = df([ row,column ])

If we want to extract multiple rows we can put row numbers in a vector and pass that vector as a row or column. If we want to extract 3 rows and all columns we can put row numbers in a vector and leave the column empty. The below example demonstrates the above statement. 

Example :

 a = df1([ c(1,2,3) ,   ]) # here we left column as empty which means we want extract all columns

If we want to extract specific columns then we can put column numbers in a vector and pass as a parameter. The below example demonstrates the above statement. 

Example :

b = df1( [ c(1,2,3) , c(1,2) ]  )

This is how indexing works. Let us see rbind() function introduction and implementation for inserting multiple rows into a dataframe.

rbind() method: rbind means row bind. Joining multiple rows with dataframe. 

Syntax: rbind(a, b)

Parameters:

• a = data frame
• b = data to be binded with data frame

Example 1 :

# creating a data frame
df1 = data.frame(num = c( 1 : 3), 
                 branch = c("IT", "CSE", "ECE"))

# creating another data frame
df2 = data.frame(num = c( 4 : 6), 
                 branch = c("EEE", "Mechanical", "civil"))

# selecting 1-2 rows , all columns from df1
new_row = df2[c(1, 2, 3),] 
# we can access data from a data frame through indexing .
# since it is a 2 dimensional one we can access data 
# by row number and column number .
# here c(1,2,3) represents row numbers and we left column
# numbers as empty . then all columns are accessed .


# new_row is appended to the df1
df1 = rbind(df1, new_row)

#printing updated data frame 
print(df1) 

Output:

Example 2: Adding rows from 3 dataframe. 

# creating one data frame
df1 = data.frame(num = c( 1 : 3 ),
                 branch = c("IT", "CSE", "ECE")) 

# creating another data frame
df2=data.frame(num = c( 4 : 6 ),
               branch = c("Chemical", "Petroleum", "Food Technology"))

df3=data.frame(num = c( 7 : 9 ),
               branch = c("EEE", "Mechanical", "Civil"))

# here we accessing 1-3 rows and all columns 
# from df2 and storing in new_row variable
new_row=df2[c(1, 2, 3),] 

# here also we are accessing 1-3 rows and all
# columns and storing in new_row2 variable
new_row2=df3[c(1, 2, 3),]

# passing data frame1 i.e., df1 and the new_row .  
df1=rbind(df1, new_row) 

# passing data frame1 i.e., df1 and new_row2
df1=rbind(df1, new_row2) 

# Here values in new_row will be appended with df1 . 
# if we pass df2,new_row ,
# the data in the nw_row will be appended with df2 
print(df1) # printing df1

 
Output: