# How to add a new column to represent the percentage for groups in an R data frame?

In data analysis, we often need to find the percentage of values that exists in a data group. This helps us to understand which value occurs frequently and which one has low frequency. Also, plotting of percentages through pie charts can be done and that gives a better view of the data to the readers. Adding a new column as percentage for groups is not a challenge if we can use mutate function of dplyr package, here you will get the examples from that.

## Example1

Live Demo

> Group<-rep(1:2,each=5)
> Frequency<-sample(1:100,10)
> df1<-data.frame(Group,Frequency)
> df1

## Output

Group Frequency
1 1 67
2 1 58
3 1 54
4 1 13
5 1 23
6 2 91
7 2 3
8 2 95
9 2 38
10 2 48

> library(dplyr)

Finding the percentage for each group values in the group −

> df1%>%group_by(Group)%>%mutate(Percentage=paste0(round(Frequency/sum(Frequency)*100,2),"%"))
# A tibble: 10 x 3
# Groups: Group [2]

## Output

Group Frequency Percentage
<int> <int> <chr>
1 1    67    31.16%
2 1    58    26.98%
3 1    54    25.12%
4 1    13    6.05%
5 1    23    10.7%
6 2    91    33.09%
7 2    3     1.09%
8 2    95    34.55%
9 2    38    13.82%
10 2   48    17.45%

## Example2

Live Demo

> Gender<-rep(c("Male","Female"),each=5)
> Salary<-sample(25000:50000,10)
> df2<-data.frame(Gender,Salary)
> df2

## Output

Gender  Salary
1  Male   41734
2  Male   39035
3  Male   36161
4  Male   33437
5  Male   45123
6  Female 44492
7  Female 48456
8  Female 31569
9  Female 35110
10 Female 43630
>df2%>%group_by(Gender)%>%mutate(Percentage=paste0(round(Salary/sum(Salary)*1
00,2),"%"))
# A tibble: 10 x 3
# Groups: Gender [2]

## Output

Gender Salary Percentage
<fct> <int> <chr>
1  Male   41734    21.35%
2  Male   39035    19.97%
3  Male   36161    18.5%
4  Male   33437    17.1%
5  Male   45123    23.08%
6  Female 44492    21.89%
7  Female 48456    23.84%
8  Female 31569    15.53%
9  Female 35110    17.27%
10 Female 43630    21.47%

## Example3

Live Demo

> Number_of_Years_in_Job<-sample(1:5,10,replace=TRUE)
> df3

## Output

1    A       4
2    A       5
3    B       4
4    B       4
5    C       1
6    C       4
7    D       1
8    D       1
9    E       3
10   E       1
ob/sum(Number_of_Years_in_Job)*100,2),"%"))
# A tibble: 10 x 3