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how to compare two network by (a) Degree centrality for every vertex (b) Closeness centrality for every vertex (c) Betweenness centrality or every vertex (d) Clustering coefficient for every vertex (e

actually i have result of two undirected unweighted graph i just have to compare for each graph for following value

(a) Degree centrality for every vertex (b) Closeness centrality for every vertex (c) Betweenness centrality or every vertex (d) Clustering coefficient for every vertex (e) Average clustering coefficient

GRAPH1  undirected unweighted graph
0   0.00779727096   0.00000000000   0.09103815439   1.00000000000 
1   0.01364522417   0.00062323294   0.09547738693   0.57142857143
2   0.01754385965   0.00359878071   0.10005851375   0.50000000000
3   0.01364522417   0.00204350305   0.09990262902   0.61904761905
4   0.01169590643   0.00045596144   0.09139497595   0.60000000000
5   0.00974658869   0.00072660153   0.09480687488   0.50000000000
6   0.00584795322   0.00011795475   0.09183673469   0.66666666667
7   0.00584795322   0.00275522523   0.09780743565   0.33333333333
8   0.01754385965   0.01006361406   0.10507988529   0.55555555556
9   0.01754385965   0.01671317309   0.10712048444   0.52777777778
10  0.01559454191   0.01835668153   0.11053652230   0.53571428571
11  0.01364522417   0.06559090579   0.11675011379   0.47619047619
12  0.01169590643   0.00522159291   0.10488652627   0.73333333333
13  0.00779727096   0.00000000000   0.09684727204   1.00000000000
14  0.01169590643   0.00012411907   0.09703045205   0.66666666667
15  0.01364522417   0.01502928511   0.11264822134   0.52380952381

GRAPH2  undirected unweighted graph
Node id, degree centrality, betweenness centrality, Closeness centrality, Clustering coefficient, Average clustering coefficient.

0 0.00722543353 0.00013607818 0.07964092531 0.80000000000
1 0.01011560694 0.00149566329 0.08282465589 0.61904761905 2 0.01156069364 0.00397149124 0.08646757466 0.50000000000 3 0.00867052023 0.00076051374 0.08621978570 0.66666666667 4 0.00867052023 0.00014090907 0.07965009208 0.73333333333 5 0.00578034682 0.00000000000 0.07652327767 0.83333333333 6 0.00578034682 0.00011414825 0.07963176064 0.83333333333 7 0.01011560694 0.00834766738 0.09017461559 0.52380952381 8 0.01156069364 0.01695964797 0.09420092567 0.42857142857 9 0.01156069364 0.01253547229 0.09443231441 0.46428571429 10 0.01156069364 0.02503457050 0.09874429224 0.35714285714 11 0.00722543353 0.00215868018 0.08643517362 0.50000000000 12 0.00578034682 0.00216583589 0.08617683686 0.50000000000 13 0.00578034682 0.00123501467 0.07961343764 0.50000000000 14 0.00433526012 0.00022719454 0.07937600367 0.66666666667 15 0.00289017341 0.00000000000 0.07375826050 1.00000000000 16 0.01011560694 0.01296515441 0.09899856938 0.52380952381 17 0.01011560694 0.00760209177 0.09923992543 0.57142857143 18 0.01011560694 0.01645097118 0.10465819722 0.57142857143 19 0.00722543353 0.00372566435 0.10395072856 0.70000000000 20 0.00722543353 0.00402976588 0.09914040115 0.70000000000 21 0.01445086705 0.02663190107 0.10937253043 0.35555555556 22 0.01300578035 0.01432494946 0.11080864692 0.50000000000

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