Comparison of two dataframes

Question

I have an excel table of 15200 lines, corresponding to a tree analyzed for its structures. I have all the structures in columns (48 structures), they have been counted on every tree. for example, the tree 12607 has 3 structures CV11, 1 structure IN12 and none (0) of the rest of all the structures. Thus, the table looks like a huge table with a lot of 0 and some numbers of the occurrence of structures on the trees. The very last column is the value given to the tree, according to the structures found on it (each structure giving a number of point to the tree by its presence on it).

The question is: Are there some structures, or combination of structures, which give a high value to the tree. Of course, according to the value of each structure, we can see which one has a higher value than the others (ex: structure CV11 has a value of 15, structure IN12 has a value of 4). But what I want to know is, if we take all the trees having a higher final value than 100 (we create a new dataframe "data100"), and we compare with the trees having a final value under 100 (we create another dataframe "data0"), can we find a significant difference in the number and occurrence of structures found on these trees? Because the structure with high value is maybe only found on the trees with a value under 100; because for example, this structure does not allow other structures to be found on the same tree.

Voilà, I hope I have given enough details... If you have any idea or proposition for solving this problem.. it will be great!

Below is my 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 ]

Sorry not clear to me, please read the info about [how to ask a good question](http://stackoverflow.com/help/how-to-ask) and how to give a [reproducible example](http://stackoverflow.com/questions/5963269). This will make it much easier for others to help you. — zx8754, Sep 11 '17 at 08:05

score 0 · Accepted Answer · answered Sep 11 '17 at 20:43

0

maybe something like this ?

library(dplyr)
data %>% group_by(ecoval > 100) %>% summarize_all(mean)

that should give you the average of each column for ecoval > and <= to 100

answered Sep 11 '17 at 20:43

moodymudskipper

46,417
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Thank you very much for your answer! I do not know very well how to interpret the result of R, what are the line FALSE and the line TRUE for? is the mean at the line named TRUE? – C.L. Sep 12 '17 at 06:34
`A tibble: 2 x 65 ecoval > 100 CV11 CV12 CV13 CV14 CV15 CV21 CV22 CV23 CV24 1 FALSE 0.00299880 0.003398641 0.0003332001 0.007530321 0.0005331201 0.005997601 0.00206584 0.003531921 0.00146608 2 TRUE 0.03314917 0.154696133 0.0441988950 0.535911602 0.0552486188 0.060773481 0.03867403 0.077348066 0.03867403` – C.L. Sep 12 '17 at 06:42
I'm grouping your rows by the condition `ecoval >100`, so the row containing `TRUE` is the row that summarize the data for `ecoval >100`, and the row containing `FALSE` contains the data for `ecoval<=100` :) – moodymudskipper Sep 12 '17 at 09:51

Comparison of two dataframes

1 Answers1