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How to Remove Rows in R DataFrame?

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  • Difficulty Level : Easy
  • Last Updated : 19 Dec, 2021
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In this article, we will discuss how to remove rows from dataframe in the R programming language.

Method 1: Remove Rows by Number

By using a particular row index number we can remove the rows.

Syntax:

data[-c(row_number), ]

where. 

  • data is the input dataframe
  • row_number is the row index position

Example:

R




# create a dataframe
data=data.frame(name=c("manoj","manoja","manoji","mano","manooj"),
                age=c(21,23,21,10,22))
  
# display by removing 4 th row
print(data[-c(4), ])
  
# display by removing 5 th row
print(data[-c(5), ])
  
# display by removing 1 st  row
print(data[-c(1), ])


Output:

> print(data[-c(4), ])
    name age
1  manoj  21
2 manoja  23
3 manoji  21
5 manooj  22
> print(data[-c(5), ])
    name age
1  manoj  21
2 manoja  23
3 manoji  21
4   mano  10
> print(data[-c(1), ])
    name age
2 manoja  23
3 manoji  21
4   mano  10
5 manooj  22

We can also remove multiple rows by using the slice operator

Syntax:

data[-c(row_number_start:row_number_end), ]

where,

  • data is the input dataframe
  • row_number_start is the starting row number
  • row_number_end is the ending row number

Example:

R




# create a dataframe
data=data.frame(name=c("manoj","manoja","manoji","mano","manooj"),
                age=c(21,23,21,10,22))
  
# display by removing row from 1 st to 4 th
print(data[-c(1:4), ])
  
# display by removing row from 1 st to 2 nd
print(data[-c(1:2), ])


Output:

    name age
5 manooj  22
>
> # display by removing row from 1 st to 2 nd
> print(data[-c(1:2), ])
   name age
3 manoji  21
4   mano  10
5 manooj  22

We can also remove multiple rows by specifying multiple row indices

Syntax:

data[-c(row numbers), ]

Example:

R




# create a dataframe
data = data.frame(name=c("manoj", "manoja", "manoji", "mano",
                         "manooj"), age=c(21, 23, 21, 10, 22))
  
# display by removing 1,3,4 rows
print(data[-c(1, 3, 4), ])


Output:

    name age
2 manoja  23
5 manooj  22

Method 2: Remove rows conditionally

We can also use the conditions using subset() function

Syntax:

subset(dataframe,condition )

Example:

R




# create a dataframe
data=data.frame(name=c("manoj","manoja","manoji","mano","manooj"),
                age=c(21,23,21,10,22))
  
# display by removing age less than 21
print(subset(data,age>21 ))


Output:

    name age
2 manoja  23
5 manooj  22

Method 3: Remove rows with NA values:

we can remove rows that contain NA values using na.omit() function from the given data frame.

Syntax:

na.omit(dataframe)

Example:

R




# create a dataframe
data=data.frame(name=c("manoj","manoja","manoji","mano","manooj"),
                age=c(21,23,21,10,22))
  
# display by removing age less than 21
print(na.omit(data))


Output:

    name age
1  manoj  21
2 manoja  23
3 manoji  21
4   mano  10
5 manooj  22

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