The post How to Remove Columns from a data frame in R appeared first on Data Science Tutorials

Remove Columns from a data frame, you may occasionally need to remove one or more columns from a data frame. Fortunately, the select() method from the dplyr package makes this simple.

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library(dplyr)

Using the data frame below, this tutorial demonstrates numerous examples of how to utilize this function in practice.

Remove Columns from a data frame

Let’s create a data frame

df <- data.frame(player = c('P1', 'P2', 'P3', 'P4', 'P5', 'P6', 'P7'),
points = c(122, 144, 154, 155, 120, 218, 229),
assists = c(43, 55, 77, 18, 114, NA,29))

Now we can view the data frame

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df
    player points assists
1     P1    122      43
2     P2    144      55
3     P3    154      77
4     P4    155      18
5     P5    120     114
6     P6    218      NA
7     P7    229      29

Approach 1: Remove Columns by Name

How to delete columns from a data frame by name is demonstrated in the following code.

delete the ‘points’ column

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df %>% select(-points)
player assists
1     P1      43
2     P2      55
3     P3      77
4     P4      18
5     P5     114
6     P6      NA
7     P7      29

Approach 2: Remove Columns in the List

The code below demonstrates how to delete columns from a data frame that belong to a certain list.

‘Points’ and ‘player’ columns should be removed.

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df %>% select(-one_of('points', 'player'))
    assists
1      43
2      55
3      77
4      18
5     114
6      NA
7      29

Approach 3: Remove Columns in Range

To remove all columns in the range from ‘position’ to ‘points,’ use the following code.

delete columns from ‘player’ to ‘points’ in the range.

df %>% select(-(player:points))
   assists
1      43
2      55
3      77
4      18
5     114
6      NA
7      29

Approach 4: Remove Columns that Contain a Phrase

The code below demonstrates how to delete all columns containing the word ‘points.’

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delete columns with the word ‘points’ in them.

df %>% select(-contains('points'))
   player assists
1     P1      43
2     P2      55
3     P3      77
4     P4      18
5     P5     114
6     P6      NA
7     P7      29

Approach 5: Remove Columns that Start with Certain Letters

To eliminate all columns that begin with the letters ‘po,’ use the following code.

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delete columns that begin with the letter ‘po’

df %>% select(-starts_with('po'))
player assists
1     P1      43
2     P2      55
3     P3      77
4     P4      18
5     P5     114
6     P6      NA
7     P7      29

Approach 6: Remove Columns that End with Certain Letters

To eliminate all columns that finish in the letter’s,’ use the following code:

‘s’-ending columns should be removed.

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df %>% select(-ends_with('s'))
    player
1     P1
2     P2
3     P3
4     P4
5     P5
6     P6
7     P7

Approach 7: Remove Columns by Position

The code below demonstrates how to remove columns from certain locations:

Columns 1 and 3 should be removed.

df %>% select(-1, -3)
   points
1    122
2    144
3    154
4    155
5    120
6    218
7    229

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