How to Use Gather Function in R (With Examples)

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The gather() function from the tidyr package can be used to “gather” a key-value pair across multiple columns.

This function uses the following basic syntax:

gather(data, key value, …)

where:

• data: Name of the data frame
• key: Name of the key column to create
• value: Name of the value column to create
• … : Specify which columns to gather from

The following examples show how to use this function in practice.

Example 1: Gather Values From Two Columns

Suppose we have the following data frame in R:

#create data frame
df frame(player=c('A', 'B', 'C', 'D'),
                 year1=c(12, 15, 19, 19),
                 year2=c(22, 29, 18, 12))

#view data frame
df

  player year1 year2
1      A    12    22
2      B    15    29
3      C    19    18
4      D    19    12

We can use the gather() function to create two new columns called “year” and “points” as follows:

library(tidyr)

#gather data from columns 2 and 3
gather(df, key="year", value="points", 2:3)

  player  year points
1      A year1     12
2      B year1     15
3      C year1     19
4      D year1     19
5      A year2     22
6      B year2     29
7      C year2     18
8      D year2     12

Example 2: Gather Values From More Than Two Columns

Suppose we have the following data frame in R:

#create data frame
df2 frame(player=c('A', 'B', 'C', 'D'),
                  year1=c(12, 15, 19, 19),
                  year2=c(22, 29, 18, 12),
                  year3=c(17, 17, 22, 25))

#view data frame
df2

  player year1 year2 year3
1      A    12    22    17
2      B    15    29    17
3      C    19    18    22
4      D    19    12    25

We can use the gather() function to “gather” the values from columns 2, 3, and 4 into two new columns called “year” and “points” as follows:

library(tidyr)

#gather data from columns 2, 3, and 4
gather(df, key="year", value="points", 2:4)

   player  year points
1       A year1     12
2       B year1     15
3       C year1     19
4       D year1     19
5       A year2     22
6       B year2     29
7       C year2     18
8       D year2     12
9       A year3     17
10      B year3     17
11      C year3     22
12      D year3     25

Additional Resources

The goal of the tidyr package is to create “tidy” data, which has the following characteristics:

• Every column is a variable.
• Every row is an observation.
• Every cell is a single value.

The tidyr package uses four core functions to create tidy data:

1. The spread() function.

2. The gather() function.

3. The separate() function.

4. The unite() function.

If you can master these four functions, you will be able to create “tidy” data from any data frame.