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How to find the sum of diagonal elements in a table in R?
The sum of diagonal elements could be required in matrix analysis therefore, we can convert the matrix into a table and find the sum of diagonal elements. This can be easily done by using sun function by extracting diagonal elements of the table using diag function. For example, if we have a table T then the sum of diagonal elements of T can be found as sum(diag(T)).
Example
Table1<-as.table(matrix(1:25,ncol=5)) Table1
Output
A B C D E A 1 6 11 16 21 B 2 7 12 17 22 C 3 8 13 18 23 D 4 9 14 19 24 E 5 10 15 20 25
Example
sum(diag(Table1))
Output
[1] 65
Example
Table2<-as.table(matrix(1:100,ncol=10)) Table2
Output
A B C D E F G H I J A 1 11 21 31 41 51 61 71 81 91 B 2 12 22 32 42 52 62 72 82 92 C 3 13 23 33 43 53 63 73 83 93 D 4 14 24 34 44 54 64 74 84 94 E 5 15 25 35 45 55 65 75 85 95 F 6 16 26 36 46 56 66 76 86 96 G 7 17 27 37 47 57 67 77 87 97 H 8 18 28 38 48 58 68 78 88 98 I 9 19 29 39 49 59 69 79 89 99 J 10 20 30 40 50 60 70 80 90 100
Example
sum(diag(Table2))
Output
[1] 505
Example
Table3<-as.table(matrix(rnorm(36),nrow=6)) Table3
Output
A B C D E F A -0.02015819 -2.14686269 -0.79392704 -0.55050284 0.23070052 0.13070019 B -0.39663252 -0.12698078 -0.09832510 -1.41939702 -0.49657164 -0.45341576 C 0.23753427 0.78309823 2.11059813 -0.41943086 -0.33058117 0.63018308 D -2.03889403 1.33432969 1.65307088 1.67585600 -1.49239102 -0.67350890 E -0.61901214 -0.89328172 1.03601932 -0.16994050 0.73360113 0.42438789 F -1.09296499 -1.10922272 0.04226664 2.58299950 0.51644977 0.41344741
Example
sum(diag(Table3))
Output
[1] -1.493482
Example
Table4<-as.table(matrix(rnorm(36,100,5),nrow=6)) Table4
Output
A B C D E F A 105.44635 93.14600 97.80468 100.68027 95.28400 100.82330 B 95.16300 98.87825 98.75319 96.53916 108.81398 99.40972 C 94.99926 105.25513 100.37713 100.96798 93.41062 101.70070 D 99.21070 99.82776 88.46770 97.40873 102.29429 95.97573 E 98.70941 95.46398 101.49608 102.96491 101.35786 105.05309 F 102.20267 101.30244 100.53210 91.06927 87.33858 102.15255
Example
sum(diag(Table4))
Output
[1] 608.7968
Example
Table5<-as.table(matrix(rnorm(25,500,50),nrow=5)) Table5
Output
A B C D E A 505.2863 493.6967 542.0539 577.7998 504.0781 B 500.1169 518.8777 403.9920 569.6609 506.1925 C 410.2091 404.1374 521.1845 547.0921 489.7272 D 520.4017 491.4741 502.0402 453.0907 490.6733 E 499.4468 520.5062 449.8988 541.2709 562.4680
Example
sum(diag(Table5))
Output
[1] 2422.402
Example
Table6<-as.table(matrix(runif(25,5,10),nrow=5)) Table6
Output
A B C D E A 9.957061 8.584646 6.731691 6.645764 6.343259 B 7.157706 5.733703 5.630403 9.290109 5.232770 C 8.244165 5.308932 5.100177 6.389525 7.758126 D 6.445069 8.942210 5.995070 6.302655 8.955960 E 8.200180 7.202910 9.770459 6.822972 6.435597
Example
sum(diag(Table6))
Output
[1] 31.74213
Example
Table7<-as.table(matrix(rexp(25,3.5),nrow=5)) Table7
Output
A B C D E A 0.29068590 0.27290414 0.55115684 0.23493220 0.51366603 B 0.69828775 0.39694271 0.08617531 0.01405418 0.29315770 C 0.07375495 0.14626855 0.36778766 0.58536517 0.38151674 D 0.02949406 0.01493486 0.23719988 0.01521633 0.03468193 E 0.08120215 0.42675242 0.33896103 0.34181323 0.06136357
Example
sum(diag(Table7))
Output
[1] 0.310424
Example
Table10<-as.table(matrix(rpois(100,15),ncol=10)) Table10
Output
A B C D E F G H I J A 22 21 16 13 10 17 10 6 11 13 B 9 13 17 15 18 8 12 17 12 12 C 22 24 17 14 15 17 12 19 18 18 D 15 15 20 19 12 17 13 14 7 16 E 18 10 15 15 6 15 13 27 22 11 F 9 14 11 8 15 10 19 12 17 14 G 17 14 13 12 11 12 14 16 12 18 H 15 18 13 18 18 20 13 15 6 20 I 16 16 15 14 12 15 9 17 14 14 J 13 20 21 13 18 17 11 16 15 15
Example
sum(diag(Table10))
Output
[1] 156
Updated on: 19-Oct-2020
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