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Drop column(s) by name from a given DataFrame in R
  • Last Updated : 26 Mar, 2021

Dropping of columns from a data frame is simply used to remove the unwanted columns in the data frame. In this article, we will be discussing the two different approaches to drop columns by name from a given Data Frame in R.

The different approaches to drop columns by the name from a data frame is R language are discussed below

Method 1: Using subset()

This is one of the easiest approaches to drop columns is by using the subset() function with the ‘-‘ sign which indicates dropping variables. This function in R Language is used to create subsets of a Data frame and can also be used to drop columns from a data frame.

  Syntax: 

subset(df, expr)



  Parameters:

  • df: Data frame used
  • expr: Condition for a subset

Approach

  • Create data frame
  • Select subset of the data to be removed
  • Put a minus sign
  • Assign to initial data frame
  • Display data frame

Example:

R




gfg <- data.frame(a=c('i','ii','iii','iv','v'),
                  x=c('I','II','III','IV','V'), 
                  y=c(1,2,3,4,5), 
                  z=c('a','b','c','d','e'))
  
print('Original dataframe:-')
gfg
  
gfg = subset(gfg, select = -c(x,z) )
print('Modified dataframe:-')
gfg

Output:

Method 2: Using names()

In this method, we are creating a character vector named drop in which we are storing column names Later we are telling R to select all the variables except the column names specified in the vector drop. The  ‘!’ sign indicates negation. 

The function names() in R Language are used to get or set the name of an Object. This function takes the object i.e. vector, matrix, or data frame as an argument along with the value that is to be assigned a name to the object. The length of the value vector passed must be exactly equal to the length of the object to be named and returns all the column names.



     Syntax

names(x) <- value

  Parameters:

  • x: Object i.e. vector, matrix, data frame, etc.
  • value: Names to be assigned to x

Approach

  • Create data frame
  • Select columns to be deleted
  • Apply negation
  • Assign it to the initial data frame
  • Display data frame

Example:

R




gfg <- data.frame(a=c('i','ii','iii','iv','v'),
                  x=c('I','II','III','IV','V'),
                  y=c(1,2,3,4,5),
                  z=c('a','b','c','d','e'))
  
print('Original dataframe:-')
gfg
  
drop <- c("x","z")
  
gfg = gfg[,!(names(gfg) %in% drop)]
print('Modified dataframe:-')
gfg

Output:

Method 3: Using select()

In this approach, we will be using select() by the import the dplyr library in R language and specifying the parameter to drop the columns of the dataset. Basically, this function keeps only the variables you mention.

Syntax:-



select(.data, …)

Parameters:-

  • data:-A data frame, data frame extension, or a lazy data frame.
  • … :- One or more unquoted expressions separated by commas. Variable names can be used as if they were positions in the data frame, so expressions like x:y can be used to select a range of variables.

Approach

  • Import module
  • Create data frame
  • Select column to be removed
  • Apply minus sign
  • Assign it to the initial data frame
  • Display data frame

Example:-

R




library(dplyr)
  
gfg <- data.frame(a=c('i','ii','iii','iv','v'), 
                  x=c('I','II','III','IV','V'), 
                  y=c(1,2,3,4,5),
                  z=c('a','b','c','d','e'))
  
print('Original dataframe:-')
gfg
  
print('Modified dataframe:-')
select(gfg, -a)

Output:-

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