# How to Use Gather Function in R?-tidyr Part2

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How to Use Gather Function in R?, To “collect” a key-value pair across many columns, use the gather() function from the tidyr package.

The basic syntax used by this function is as follows.

gather(data, key value, …)

where:

**data**: Name of the data frame

**key**: Name of the key column to create

**value**: Name of the newly created value column

**…** : Choose which columns to collect data from.

## How to Use Gather Function in R

The practical application of this function is demonstrated in the examples that follow.

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### Example 1: Gather Values From Two Columns

Let’s say we have the R data frame shown below:

make a data frame

df <- data.frame(player=c('P1', 'P2', 'P3', 'P4'), year1=c(212, 215, 319, 129), year2=c(232, 229, 158, 122))

Let’s view the data frame

df player year1 year2 1 P1 212 232 2 P2 215 229 3 P3 319 158 4 P4 129 122

The gather() function can be used to add two new columns named “year” and “points,” respectively:

library(tidyr)

get information from columns 2 and 3

gather(df, key="year", value="points", 2:3) player year points 1 P1 year1 212 2 P2 year1 215 3 P3 year1 319 4 P4 year1 129 5 P1 year2 232 6 P2 year2 229 7 P3 year2 158 8 P4 year2 122

### Example 2: Collect Information From More Than Two Columns

Let’s say we have the R data frame shown below:

Let’s create a data frame

df2 <- data.frame(player=c('P1', 'P2', 'P3', 'P4'), year1=c(213, 112, 112, 114), year2=c(122, 229, 215, 211), year3=c(123, 122, 122, 129))

Now we can view the data frame

df2 player year1 year2 year3 1 P1 213 122 123 2 P2 112 229 122 3 P3 112 215 122 4 P4 114 211 129

The data from columns 2, 3, and 4 can be “gathered” into two additional columns called “year” and “points” using the gather() method as follows:

library(tidyr)

assemble information from columns 2, 3, and 4.

gather(df2, key="year", value="points", 2:4) player year points 1 P1 year1 213 2 P2 year1 112 3 P3 year1 112 4 P4 year1 114 5 P1 year2 122 6 P2 year2 229 7 P3 year2 215 8 P4 year2 211 9 P1 year3 123 10 P2 year3 122 11 P3 year3 122 12 P4 year3 129

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