# How to add proportion total at margins on a table in R?

R ProgrammingServer Side ProgrammingProgramming

The proportion total in a table helps us to understand the contribution of each row and each column in the total. Therefore, if we want to find the proportion total at margins, we can use addmargins function if we have the proportion table and if we do not have that table then firstly it needs to be created and then use the addmargins function. For example, if we have a proportion table called prop then the command will be addmargins(prop).

## Example1

Consider the below table of proportions −

Live Demo

> x1<-rpois(5,2)
> x2<-rpois(5,2)
> x3<-rpois(5,2)
> x4<-rpois(5,2)
> x5<-rpois(5,2)
> x6<-rpois(5,2)
> x7<-rpois(5,2)
> x8<-rpois(5,2)
> table1<-prop.table(rbind(x1,x2,x3,x4,x5,x6,x7,x8))
> table1

## Output

         [,1]       [,2]       [,3]       [,4]       [,5]
x1 0.07692308 0.01538462 0.01538462 0.00000000 0.06153846
x2 0.01538462 0.01538462 0.03076923 0.01538462 0.01538462
x3 0.00000000 0.01538462 0.01538462 0.01538462 0.01538462
x4 0.06153846 0.00000000 0.07692308 0.00000000 0.03076923
x5 0.06153846 0.01538462 0.03076923 0.03076923 0.00000000
x6 0.03076923 0.06153846 0.03076923 0.01538462 0.01538462
x7 0.00000000 0.04615385 0.00000000 0.01538462 0.03076923
x8 0.04615385 0.01538462 0.00000000 0.01538462 0.04615385

> addmargins(table1)

## Output

                                                                  Sum
x1  0.07692308 0.01538462 0.01538462 0.00000000 0.06153846 0.16923077
x2  0.01538462 0.01538462 0.03076923 0.01538462 0.01538462 0.09230769
x3  0.00000000 0.01538462 0.01538462 0.01538462 0.01538462 0.06153846
x4  0.06153846 0.00000000 0.07692308 0.00000000 0.03076923 0.16923077
x5  0.06153846 0.01538462 0.03076923 0.03076923 0.00000000 0.13846154
x6  0.03076923 0.06153846 0.03076923 0.01538462 0.01538462 0.15384615
x7  0.00000000 0.04615385 0.00000000 0.01538462 0.03076923 0.09230769
x8  0.04615385 0.01538462 0.00000000 0.01538462 0.04615385 0.12307692
Sum 0.29230769 0.18461538 0.20000000 0.10769231 0.21538462 1.00000000

## Example2

Live Demo

> y1<-rpois(20,4)
> y2<-rpois(20,4)
> y3<-rpois(20,4)
> df_y<-data.frame(y1,y2,y3)
> df_y

## Output

   y1 y2 y3
1   6  3  4
2   6  6  8
3   4  3  5
4   5  6  3
5   2  3  1
6   4  4  5
7   2  4  7
8   2  1  3
9   8  6  6
10  2  5  4
11  3  7  1
12  3  3  4
13  6  4  3
14  4  3  1
15  2  3  2
16  2  1  6
17  4  5  2
18  4  5  3
19  7  6  5
20  3  5  3

## Example

> table2<-prop.table(as.matrix(df_y))
> table2

## Output

               y1          y2          y3
[1,] 0.025210084 0.012605042 0.016806723
[2,] 0.025210084 0.025210084 0.033613445
[3,] 0.016806723 0.012605042 0.021008403
[4,] 0.021008403 0.025210084 0.012605042
[5,] 0.008403361 0.012605042 0.004201681
[6,] 0.016806723 0.016806723 0.021008403
[7,] 0.008403361 0.016806723 0.029411765
[8,] 0.008403361 0.004201681 0.012605042
[9,] 0.033613445 0.025210084 0.025210084
[10,] 0.008403361 0.021008403 0.016806723
[11,] 0.012605042 0.029411765 0.004201681
[12,] 0.012605042 0.012605042 0.016806723
[13,] 0.025210084 0.016806723 0.012605042
[14,] 0.016806723 0.012605042 0.004201681
[15,] 0.008403361 0.012605042 0.008403361
[16,] 0.008403361 0.004201681 0.025210084
[17,] 0.016806723 0.021008403 0.008403361
[18,] 0.016806723 0.021008403 0.012605042
[19,] 0.029411765 0.025210084 0.021008403
[20,] 0.012605042 0.021008403 0.012605042

> addmargins(table2)

## Output

             y1          y2          y3        Sum
0.025210084 0.012605042 0.016806723 0.05462185
0.025210084 0.025210084 0.033613445 0.08403361
0.016806723 0.012605042 0.021008403 0.05042017
0.021008403 0.025210084 0.012605042 0.05882353
0.008403361 0.012605042 0.004201681 0.02521008
0.016806723 0.016806723 0.021008403 0.05462185
0.008403361 0.016806723 0.029411765 0.05462185
0.008403361 0.004201681 0.012605042 0.02521008
0.033613445 0.025210084 0.025210084 0.08403361
0.008403361 0.021008403 0.016806723 0.04621849
0.012605042 0.029411765 0.004201681 0.04621849
0.012605042 0.012605042 0.016806723 0.04201681
0.025210084 0.016806723 0.012605042 0.05462185
0.016806723 0.012605042 0.004201681 0.03361345
0.008403361 0.012605042 0.008403361 0.02941176
0.008403361 0.004201681 0.025210084 0.03781513
0.016806723 0.021008403 0.008403361 0.04621849
0.016806723 0.021008403 0.012605042 0.05042017
0.029411765 0.025210084 0.021008403 0.07563025
0.012605042 0.021008403 0.012605042 0.04621849
Sum 0.331932773 0.348739496 0.319327731 1.00000000
Updated on 05-Mar-2021 07:08:14