r - Comparison of two dataframes -
i have excel table of 15200 lines, corresponding tree analyzed structures. have structures in columns (48 structures), have been counted on every tree. example, tree 12607 has 3 structures cv11, 1 structure in12 , none (0) of rest of structures. thus, table looks huge table lot of 0 , numbers of occurrence of structures on trees. last column value given tree, according structures found on (each structure giving number of point tree presence on it).
the question is: there structures, or combination of structures, give high value tree. of course, according value of each structure, can see 1 has higher value others (ex: structure cv11 has value of 15, structure in12 has value of 4). want know is, if take trees having higher final value 100 (we create new dataframe "data100"), , compare trees having final value under 100 (we create dataframe "data0"), can find significant difference in number , occurrence of structures found on these trees? because structure high value maybe found on trees value under 100; because example, structure not allow other structures found on same tree.
voilà, hope have given enough details... if have idea or proposition solving problem.. great!
below script.
> data100 cv11 cv12 cv13 cv14 cv15 cv21 cv22 cv23 cv24 cv25 cv26 cv31 cv32 cv33 cv41 cv42 cv43 cv44 cv51 cv52 in11 in12 in13 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 13 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 in14 in21 in22 in23 in31 in32 in33 in34 ba11 ba12 ba21 de11 de12 de13 de14 de15 gr11 gr12 gr13 gr21 gr22 gr31 gr32 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ep11 ep12 ep13 ep14 ep21 ep31 ep32 ep33 ep34 ep35 ne11 ne12 ne21 ot11 ot12 ot21 ot22 ecoval 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 56 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 63 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 77 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 54 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 [ reached getoption("max.print") -- omitted 60749 rows ] > sortdata100<-data100[order(data100[,64],decreasing=t),] > rsortdata100<-sortdata100[sortdata100$ecoval>100,] > rsortdata100<-na.omit(rsortdata100)#181 lignes > rsortdata100 cv11 cv12 cv13 cv14 cv15 cv21 cv22 cv23 cv24 cv25 cv26 cv31 cv32 cv33 cv41 cv42 cv43 cv44 cv51 cv52 in11 in12 in13 1291 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1083 0 4 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3919 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 14685 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4021 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 5452 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14686 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 4022 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1013 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2895 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4719 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 682 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3444 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1299 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2713 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 in14 in21 in22 in23 in31 in32 in33 in34 ba11 ba12 ba21 de11 de12 de13 de14 de15 gr11 gr12 gr13 gr21 gr22 gr31 gr32 1291 0 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1083 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3919 0 0 1 0 2 0 0 0 2 0 0 0 3 0 0 0 0 0 0 11 0 0 0 14685 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4021 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5452 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 14686 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 2 4022 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1013 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2895 0 0 0 1 0 0 0 0 4 0 0 3 0 4 3 0 0 0 0 0 0 0 0 4719 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 682 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 3444 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1299 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 2713 0 0 0 2 0 3 0 0 2 0 0 0 1 5 1 0 0 0 0 0 0 0 0 ep11 ep12 ep13 ep14 ep21 ep31 ep32 ep33 ep34 ep35 ne11 ne12 ne21 ot11 ot12 ot21 ot22 ecoval 1291 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1192 1083 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 424 3919 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 380 14685 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 370 4021 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 358 5452 0 0 0 0 0 0 1 0 0 11 0 0 0 0 1 0 0 356 14686 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 354 4022 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 346 1013 0 8 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 326 2895 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 325 4719 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 324 682 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 311 3444 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 306 1299 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 302 2713 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 302 [ reached getoption("max.print") -- omitted 166 rows ] > data0<-sortdata100[sortdata100$ecoval<100,] > data0<-na.omit(data0) > data0 cv11 cv12 cv13 cv14 cv15 cv21 cv22 cv23 cv24 cv25 cv26 cv31 cv32 cv33 cv41 cv42 cv43 cv44 cv51 cv52 in11 in12 in13 4728 0 0 0 1 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 5339 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 11766 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 796 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3561 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 10581 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 10618 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0 0 0 0 14376 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 14389 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 790 0 0 0 1 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 3974 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4739 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 156 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2740 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2950 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 in14 in21 in22 in23 in31 in32 in33 in34 ba11 ba12 ba21 de11 de12 de13 de14 de15 gr11 gr12 gr13 gr21 gr22 gr31 gr32 4728 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 5339 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 11766 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 796 1 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3561 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10581 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 10618 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 14376 1 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 14389 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 790 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 3974 0 0 0 0 0 0 0 0 1 0 0 0 4 0 0 0 1 0 0 0 0 0 0 4739 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 156 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2740 0 0 0 0 0 0 0 0 0 0 0 0 0 6 2 0 0 0 0 0 0 0 0 2950 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ep11 ep12 ep13 ep14 ep21 ep31 ep32 ep33 ep34 ep35 ne11 ne12 ne21 ot11 ot12 ot21 ot22 ecoval 4728 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 99 5339 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 99 11766 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 99 796 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 98 3561 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 98 10581 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 98 10618 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 98 14376 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 98 14389 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 98 790 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 97 3974 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 97 4739 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 97 156 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 96 2740 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 96 2950 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 96 [ reached getoption("max.print") -- omitted 14984 rows ]
maybe ?
library(dplyr) data %>% group_by(ecoval > 100) %>% summarize_all(mean) that should give average of each column ecoval > , <= 100
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