Why R is giving me different sums and counts of rows than Excel?

riokoto80 · March 24, 2020, 6:00pm

I've discovered an issue when calculating sum of rows and counts (">0") in my data frame. I'm trying to sum rows to have abundance and richness of a community data "spe" (51 columns(taxa) and 82 rows(sites)). I realize this when double checking the sums and counts in R and Excel. Why is this happening? This is the code I use in R:
For Sum:
apply(spe[,-1],1,sum)
For Counts:
apply(spe[,-1]>0,1,sum)

I've noticed the first rows goes well with the sums and counts, but then the results in R are different by subtracting numbers in sums and just 1 less in the counts issue, and after some rows, there are some good with the sums and counts but not all of them comparing to Excel. Why is that happening? Can someone help me please? Thanks in advance.

spe<-data.frame(read.table("~/Dropbox/Docs Redro/Paper Tesis MBC/MBC_SPP_ALL.csv", sep=",", header=TRUE, row.names=1))
head(spe)
#>   Duge Allua1 Ande Anom Atop1 Atop2 Bleph1 Bleph2 Bleph3 Caillo2 Caillo3
#> 2    0      0    0    0     1     0      0      0      0       0       0
#> 3    0      0    0    0     0     0      0      0      0       0       0
#> 4    0      0    0    0     0     0      0      0      0       0       0
#> 5    0      0    0    0     0     0      0      0      0       0       0
#> 8    0      0    0    0     0     0      0      0      0       0       0
#> 9    0      0    0    0     0     0      0      0      0       0       0
#>   Caillo1 Ceratoindet Cheli2 chiroindet Chiroinae Claudio Contu Corix2 Crambi
#> 2       2           0      1          0         0       0     0      0      0
#> 3       0           0      0          0         0       0     0      0      0
#> 4       3           0      2          0         0       0     0      0      0
#> 5       0           0      0          0         0       0     0      0      0
#> 8       6           0      0          0         0       0     0      0      0
#> 9       0           0      0          0         0       0     0      0      0
#>   Curcu1 Curcu2 Diame1 Diame2 Dimec Dytis1 Ephyd2 Geran Helicho Hemer1 Hyale
#> 2      0      0      1      0     0      0      0     0       0      2     0
#> 3      0      0      0      0     0      0      0     0       0      0     0
#> 4      0      0      2      1     0      0      0     0       0      1     0
#> 5      0      0      0      0     0      0      0     0       0      0     0
#> 8      0      0      0      0     0      1      0     0       0      0     0
#> 9      0      0      1      0     0      0      0     0       0      0     0
#>   HYDRA Hydrosc Leech1 Leech2 Leech3 Leech4 Leuco Limoniindet Lumbri Lymnae
#> 2     0       0      0      0      0      0     0           0      0      0
#> 3     0       0      0      0      0      0     0           0      0      0
#> 4     0       0      0      0      2      0     0           0      0      0
#> 5     0       0      0      0      0      0     0           0      0      0
#> 8     0       0      0      0      0      0     0           0      0      0
#> 9     0       0      0      0      0      0     0           0      0      0
#>   Maya Molo1 Molo2 Morto Musci5 Musci6 Musci7 Musci4 Musci1 Musci2 Musci3 Naid1
#> 2    0     1     0     0      0      0      0      1     11      0      0    39
#> 3    0     0     0     0      0      0      0      0      0      0      0     0
#> 4    0     0     0     0      0      0      0      0      8      0      0    32
#> 5    0     0     0     0      0      0      0      1      0      0      0     0
#> 8    0     0     1     0      0      0      0      0      2      0      0     0
#> 9    0     0     0     0      0      0      0      0      0      0      0     0
#>   Naid2 Naid3 Nectop Nema Neoel1 Neoel2 Neot Nepti Nona1 Ochro Ortho Ostra
#> 2     0     0      0    2      0      0    0     0     0     0    72     0
#> 3     0     0      0    0      0      0    0     0     0     0     0     0
#> 4     0     0      0    4      0      1    0     0     0     0    85     0
#> 5     0     0      0    0      0      0    0     0     0     0     7     0
#> 8     0     0      0    2      0      0    0     0     0     0    43     0
#> 9     0     0      0    0      0      0    0     0     0     0     2     0
#>   Podo1 Podo2 Podo3 Podo4 Priono1 Priono2 Priono3 Schoe Simu1 Sphae Staphy1
#> 2    24     0     4     1       0       0       0     0   124     0       1
#> 3    16     0    28     0       0       0       0     0     0     0       0
#> 4   177     0     2     2       0       0       0     0    18     0       0
#> 5    13     0    71     1       0       0       0     0     0     0       0
#> 8    46     0     3     0       0       0       0     0     3     0       0
#> 9    49     0    20    14       0       0       0     0     0     0       1
#>   Staphy2 Stilo1 Sync1 Tanyp Tipu Trichoco
#> 2       0      0     0     0    0        0
#> 3       0      0     0     0    0        0
#> 4       0      0     0     0    0        0
#> 5       0      0     0     0    0        0
#> 8       0      0     0     0    0        0
#> 9       0      0     0     0    0        0

# Spp Richness
apply(spe[,-1]>0,1,sum)
#>  2  3  4  5  8  9  1  7 37 38 47 24 46 43 45 50 40 42 14 49 51 29 30 31 33  6 
#> 16  2 15  5  9  6 17 17 10 15 19 33 27 34 31 27 20 25 32 29 30 26 35 34 25 20 
#> 41 26 27 34 35 10 15 16 17 18 19 20 21 22 25 28 32 36 48 13 12 11 23 39 44 
#> 24 22 24 29 26 18 25 26 24 33 26 24 16 27 21 36 14 31 25 33 15 27 30 17 21

# Abundance
apply(spe[,-1],1,sum)
#>    2    3    4    5    8    9    1    7   37   38   47   24   46   43   45   50 
#>  287   44  340   93  107   87  214  268  112   58  788 1554 1225 2683  990 2757 
#>   40   42   14   49   51   29   30   31   33    6   41   26   27   34   35   10 
#>  213  348 1508 1479 1459 1026 2961 2807 2586  760  629 2074 1254 2104 9976  531 
#>   15   16   17   18   19   20   21   22   25   28   32   36   48   13   12   11 
#> 1645 4161 1371 4132 1407 3807 4047 1619 4314 3057  232 3348 1457 1633 2240 2084 
#>   23   39   44 
#> 1734  553 2774

dput(head(spe))
#> structure(list(Duge = c(0L, 0L, 0L, 0L, 0L, 0L), Allua1 = c(0L, 
#> 0L, 0L, 0L, 0L, 0L), Ande = c(0L, 0L, 0L, 0L, 0L, 0L), Anom = c(0L, 
#> 0L, 0L, 0L, 0L, 0L), Atop1 = c(1L, 0L, 0L, 0L, 0L, 0L), Atop2 = c(0L, 
#> 0L, 0L, 0L, 0L, 0L), Bleph1 = c(0L, 0L, 0L, 0L, 0L, 0L), Bleph2 = c(0L, 
#> 0L, 0L, 0L, 0L, 0L), Bleph3 = c(0L, 0L, 0L, 0L, 0L, 0L), Caillo2 = c(0L, 
#> 0L, 0L, 0L, 0L, 0L), Caillo3 = c(0L, 0L, 0L, 0L, 0L, 0L), Caillo1 = c(2L, 
#> 0L, 3L, 0L, 6L, 0L), Ceratoindet = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Cheli2 = c(1L, 0L, 2L, 0L, 0L, 0L), chiroindet = c(0L, 0L, 
#>     0L, 0L, 0L, 0L), Chiroinae = c(0L, 0L, 0L, 0L, 0L, 0L), Claudio = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Contu = c(0L, 0L, 0L, 0L, 0L, 0L), Corix2 = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Crambi = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Curcu1 = c(0L, 0L, 0L, 0L, 0L, 0L), Curcu2 = c(0L, 0L, 0L, 
#>     0L, 0L, 0L), Diame1 = c(1L, 0L, 2L, 0L, 0L, 1L), Diame2 = c(0L, 
#>     0L, 1L, 0L, 0L, 0L), Dimec = c(0L, 0L, 0L, 0L, 0L, 0L), Dytis1 = c(0L, 
#>     0L, 0L, 0L, 1L, 0L), Ephyd2 = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Geran = c(0L, 0L, 0L, 0L, 0L, 0L), Helicho = c(0L, 0L, 0L, 
#>     0L, 0L, 0L), Hemer1 = c(2L, 0L, 1L, 0L, 0L, 0L), Hyale = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), HYDRA = c(0L, 0L, 0L, 0L, 0L, 0L), Hydrosc = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Leech1 = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Leech2 = c(0L, 0L, 0L, 0L, 0L, 0L), Leech3 = c(0L, 0L, 2L, 
#>     0L, 0L, 0L), Leech4 = c(0L, 0L, 0L, 0L, 0L, 0L), Leuco = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Limoniindet = c(0L, 0L, 0L, 0L, 0L, 
#>     0L), Lumbri = c(0L, 0L, 0L, 0L, 0L, 0L), Lymnae = c(0L, 0L, 
#>     0L, 0L, 0L, 0L), Maya = c(0L, 0L, 0L, 0L, 0L, 0L), Molo1 = c(1L, 
#>     0L, 0L, 0L, 0L, 0L), Molo2 = c(0L, 0L, 0L, 0L, 1L, 0L), Morto = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Musci5 = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Musci6 = c(0L, 0L, 0L, 0L, 0L, 0L), Musci7 = c(0L, 0L, 0L, 
#>     0L, 0L, 0L), Musci4 = c(1L, 0L, 0L, 1L, 0L, 0L), Musci1 = c(11L, 
#>     0L, 8L, 0L, 2L, 0L), Musci2 = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Musci3 = c(0L, 0L, 0L, 0L, 0L, 0L), Naid1 = c(39L, 0L, 32L, 
#>     0L, 0L, 0L), Naid2 = c(0L, 0L, 0L, 0L, 0L, 0L), Naid3 = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Nectop = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Nema = c(2L, 0L, 4L, 0L, 2L, 0L), Neoel1 = c(0L, 0L, 0L, 
#>     0L, 0L, 0L), Neoel2 = c(0L, 0L, 1L, 0L, 0L, 0L), Neot = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Nepti = c(0L, 0L, 0L, 0L, 0L, 0L), Nona1 = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Ochro = c(0L, 0L, 0L, 0L, 0L, 0L), Ortho = c(72L, 
#>     0L, 85L, 7L, 43L, 2L), Ostra = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Podo1 = c(24L, 16L, 177L, 13L, 46L, 49L), Podo2 = c(0L, 0L, 
#>     0L, 0L, 0L, 0L), Podo3 = c(4L, 28L, 2L, 71L, 3L, 20L), Podo4 = c(1L, 
#>     0L, 2L, 1L, 0L, 14L), Priono1 = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Priono2 = c(0L, 0L, 0L, 0L, 0L, 0L), Priono3 = c(0L, 0L, 
#>     0L, 0L, 0L, 0L), Schoe = c(0L, 0L, 0L, 0L, 0L, 0L), Simu1 = c(124L, 
#>     0L, 18L, 0L, 3L, 0L), Sphae = c(0L, 0L, 0L, 0L, 0L, 0L), 
#>     Staphy1 = c(1L, 0L, 0L, 0L, 0L, 1L), Staphy2 = c(0L, 0L, 
#>     0L, 0L, 0L, 0L), Stilo1 = c(0L, 0L, 0L, 0L, 0L, 0L), Sync1 = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Tanyp = c(0L, 0L, 0L, 0L, 0L, 0L), Tipu = c(0L, 
#>     0L, 0L, 0L, 0L, 0L), Trichoco = c(0L, 0L, 0L, 0L, 0L, 0L)), row.names = c(2L, 
#> 3L, 4L, 5L, 8L, 9L), class = "data.frame")

^{Created on 2020-03-24 by the reprex package (v0.3.0)}

andresrcs · March 24, 2020, 6:12pm

Hi!

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners Guides & FAQs

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

riokoto80 · March 24, 2020, 6:56pm

Now I've added a minimal dataset using reprex, thanks a lot.

clausp · March 24, 2020, 9:02pm

I think @andresrcs is looking for an actual data set. We do not have access to your file and, therefore, cannot run your code. The reproducible example should, ideally, be completely self-contained.

andresrcs · March 24, 2020, 9:17pm

I can't reproduce your issue, I get exactly the same results on R and Excel with your sample data.

spe <- structure(list(Duge = c(0L, 0L, 0L, 0L, 0L, 0L), Allua1 = c(0L, 
 0L, 0L, 0L, 0L, 0L), Ande = c(0L, 0L, 0L, 0L, 0L, 0L), Anom = c(0L, 
 0L, 0L, 0L, 0L, 0L), Atop1 = c(1L, 0L, 0L, 0L, 0L, 0L), Atop2 = c(0L, 
 0L, 0L, 0L, 0L, 0L), Bleph1 = c(0L, 0L, 0L, 0L, 0L, 0L), Bleph2 = c(0L, 
 0L, 0L, 0L, 0L, 0L), Bleph3 = c(0L, 0L, 0L, 0L, 0L, 0L), Caillo2 = c(0L, 
 0L, 0L, 0L, 0L, 0L), Caillo3 = c(0L, 0L, 0L, 0L, 0L, 0L), Caillo1 = c(2L, 
 0L, 3L, 0L, 6L, 0L), Ceratoindet = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Cheli2 = c(1L, 0L, 2L, 0L, 0L, 0L), chiroindet = c(0L, 0L, 
     0L, 0L, 0L, 0L), Chiroinae = c(0L, 0L, 0L, 0L, 0L, 0L), Claudio = c(0L, 
     0L, 0L, 0L, 0L, 0L), Contu = c(0L, 0L, 0L, 0L, 0L, 0L), Corix2 = c(0L, 
     0L, 0L, 0L, 0L, 0L), Crambi = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Curcu1 = c(0L, 0L, 0L, 0L, 0L, 0L), Curcu2 = c(0L, 0L, 0L, 
     0L, 0L, 0L), Diame1 = c(1L, 0L, 2L, 0L, 0L, 1L), Diame2 = c(0L, 
     0L, 1L, 0L, 0L, 0L), Dimec = c(0L, 0L, 0L, 0L, 0L, 0L), Dytis1 = c(0L, 
     0L, 0L, 0L, 1L, 0L), Ephyd2 = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Geran = c(0L, 0L, 0L, 0L, 0L, 0L), Helicho = c(0L, 0L, 0L, 
     0L, 0L, 0L), Hemer1 = c(2L, 0L, 1L, 0L, 0L, 0L), Hyale = c(0L, 
     0L, 0L, 0L, 0L, 0L), HYDRA = c(0L, 0L, 0L, 0L, 0L, 0L), Hydrosc = c(0L, 
     0L, 0L, 0L, 0L, 0L), Leech1 = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Leech2 = c(0L, 0L, 0L, 0L, 0L, 0L), Leech3 = c(0L, 0L, 2L, 
     0L, 0L, 0L), Leech4 = c(0L, 0L, 0L, 0L, 0L, 0L), Leuco = c(0L, 
     0L, 0L, 0L, 0L, 0L), Limoniindet = c(0L, 0L, 0L, 0L, 0L, 
     0L), Lumbri = c(0L, 0L, 0L, 0L, 0L, 0L), Lymnae = c(0L, 0L, 
     0L, 0L, 0L, 0L), Maya = c(0L, 0L, 0L, 0L, 0L, 0L), Molo1 = c(1L, 
     0L, 0L, 0L, 0L, 0L), Molo2 = c(0L, 0L, 0L, 0L, 1L, 0L), Morto = c(0L, 
     0L, 0L, 0L, 0L, 0L), Musci5 = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Musci6 = c(0L, 0L, 0L, 0L, 0L, 0L), Musci7 = c(0L, 0L, 0L, 
     0L, 0L, 0L), Musci4 = c(1L, 0L, 0L, 1L, 0L, 0L), Musci1 = c(11L, 
     0L, 8L, 0L, 2L, 0L), Musci2 = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Musci3 = c(0L, 0L, 0L, 0L, 0L, 0L), Naid1 = c(39L, 0L, 32L, 
     0L, 0L, 0L), Naid2 = c(0L, 0L, 0L, 0L, 0L, 0L), Naid3 = c(0L, 
     0L, 0L, 0L, 0L, 0L), Nectop = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Nema = c(2L, 0L, 4L, 0L, 2L, 0L), Neoel1 = c(0L, 0L, 0L, 
     0L, 0L, 0L), Neoel2 = c(0L, 0L, 1L, 0L, 0L, 0L), Neot = c(0L, 
     0L, 0L, 0L, 0L, 0L), Nepti = c(0L, 0L, 0L, 0L, 0L, 0L), Nona1 = c(0L, 
     0L, 0L, 0L, 0L, 0L), Ochro = c(0L, 0L, 0L, 0L, 0L, 0L), Ortho = c(72L, 
     0L, 85L, 7L, 43L, 2L), Ostra = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Podo1 = c(24L, 16L, 177L, 13L, 46L, 49L), Podo2 = c(0L, 0L, 
     0L, 0L, 0L, 0L), Podo3 = c(4L, 28L, 2L, 71L, 3L, 20L), Podo4 = c(1L, 
     0L, 2L, 1L, 0L, 14L), Priono1 = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Priono2 = c(0L, 0L, 0L, 0L, 0L, 0L), Priono3 = c(0L, 0L, 
     0L, 0L, 0L, 0L), Schoe = c(0L, 0L, 0L, 0L, 0L, 0L), Simu1 = c(124L, 
     0L, 18L, 0L, 3L, 0L), Sphae = c(0L, 0L, 0L, 0L, 0L, 0L), 
     Staphy1 = c(1L, 0L, 0L, 0L, 0L, 1L), Staphy2 = c(0L, 0L, 
     0L, 0L, 0L, 0L), Stilo1 = c(0L, 0L, 0L, 0L, 0L, 0L), Sync1 = c(0L, 
     0L, 0L, 0L, 0L, 0L), Tanyp = c(0L, 0L, 0L, 0L, 0L, 0L), Tipu = c(0L, 
     0L, 0L, 0L, 0L, 0L), Trichoco = c(0L, 0L, 0L, 0L, 0L, 0L)), row.names = c(2L, 
 3L, 4L, 5L, 8L, 9L), class = "data.frame")

rowSums(spe[,-1])
#>   2   3   4   5   8   9 
#> 287  44 340  93 107  87

rowSums(spe[,-1] > 0)
#>  2  3  4  5  8  9 
#> 16  2 15  5  9  6

riokoto80 · March 24, 2020, 9:17pm

Ok, but how do I upload my data file here? I think .xls or .csv is not allowed

andresrcs · March 24, 2020, 9:18pm

You can upload the file to a cloud storage service (e.g. Dropbx, Google Drive, Box, etc) and post a link.

riokoto80 · March 24, 2020, 9:21pm

Yes, but look at the entire data set, since row 13 there are a mistakes in sums and counts:

andresrcs · March 24, 2020, 9:24pm

Well then, try to share sample data that reproduces your issue, if I can't reproduce, I can't see what is going on and help you.

riokoto80 · March 24, 2020, 9:31pm

Good, but how can I share with you my sample data? Here in upload, I cannot upload csv or xls files

andresrcs · March 24, 2020, 9:34pm

riokoto80 · March 24, 2020, 9:35pm

Here it is with reprex:

spe<-data.frame(read.table("~/Dropbox/Docs Redro/Paper Tesis MBC/MBC_SPP_ALL.csv", sep=",", header=TRUE, row.names=1))
spe
#>    Duge Allua1 Ande Anom Atop1 Atop2 Bleph1 Bleph2 Bleph3 Caillo2 Caillo3
#> 2     0      0    0    0     1     0      0      0      0       0       0
#> 3     0      0    0    0     0     0      0      0      0       0       0
#> 4     0      0    0    0     0     0      0      0      0       0       0
#> 5     0      0    0    0     0     0      0      0      0       0       0
#> 8     0      0    0    0     0     0      0      0      0       0       0
#> 9     0      0    0    0     0     0      0      0      0       0       0
#> 1     0      7   15    0     1     0      0      0      0       0       0
#> 7     0     11   48    0     4     0      1      0      0       0       0
#> 37    0      0   10    0     2     0      0      0      0       0       0
#> 38    0      6   11    0     0     0      0      0      0       0       0
#> 47   21    173  165    0     9     0      0      0      0       0       0
#> 24  100     85  774    0     6     0      0      0      0       0       0
#> 46    8    369  189    0     7     0      0      0      0       0       0
#> 43    3    161 1032   11    12     0      2      0      0       0       0
#> 45    4     26  354    4     0     0      0      0      0       0       0
#> 50   26    245 1146    0     8     0      4      0      2       0       0
#> 40   13      8   40    1     7     0      1      0      0       0       0
#> 42   15      4   51   29     5     0     94      0      0       0       0
#> 14    2      7  175  122     5     0     11      0      0       0       0
#> 49   18      2  686  103     5     0      0      0      0       0       0
#> 51    2     21  223   90     0     0     17      9      3       0       0
#> 29    2      0  165   88     4     0     19      0      0       1       0
#> 30    8      3  470   28     2     0      3      0      0       0       0
#> 31   16      1   34   22     3     0      7      3      0       0       3
#> 33    9      1   51   30     0     0      0      0      0       1       0
#> 6     0     56   72    0     8     0      0      0      0       0       0
#> 41   16      8  139  154     8     0      0      0      0       0       0
#> 26    2     52 1445    2     1     0      0      0      0       0       0
#> 27   31     81  369   62     2     0      0      0      0       0       0
#> 34   22    194  149    1     8     1      4      0      0       0       0
#> 35   74      8  127   23     1     0      0      0      0       0       0
#> 10    3      0  108   26     2     0      0      0      0       0       0
#> 15   49      0   11  438     0     2      0      0      0       0       0
#> 16   41      3  164  183     0     0      0      0      0       0       0
#> 17    8      0   53   62     0     0      0      0      0       0       0
#> 18    3    298   17   11     0     0      0      0      0       3       0
#> 19    0     29  198   35    15     0      0      0      0       0       0
#> 20   48      7  774    0    17     0      0      0      0       0       0
#> 21    2      0    0    4     0     0      0      0      0       0       0
#> 22   45      0  542  174     1     0      0      0      0       0       0
#> 25   81    121   14    0     0     0      0      0      0       0       0
#> 28   34      7  597    0     3     0     62      3      0       0       0
#> 32    0      0    2    0     0     0      0      0      0       0       0
#> 36   19    124  113   82    15     0      0      0      0       0       0
#> 48    1      5   28    0    36     0      0      0      0       0       0
#> 13   99      3  173  226     1     0      0      0      0       0       0
#> 12  160      0 1085  365    20     0      0      0      0       0       0
#> 11   32      0    9    3     0     0      0      0      0       0       0
#> 23   99      0  252    5     1     0      0      0      0       1       0
#> 39    2      0   99    0     3     0      0      0      0       0       0
#> 44   23      0  518  191     0     0      0      0      0       0       0
#>    Caillo1 Ceratoindet Cheli2 chiroindet Chiroinae Claudio Contu Corix2 Crambi
#> 2        2           0      1          0         0       0     0      0      0
#> 3        0           0      0          0         0       0     0      0      0
#> 4        3           0      2          0         0       0     0      0      0
#> 5        0           0      0          0         0       0     0      0      0
#> 8        6           0      0          0         0       0     0      0      0
#> 9        0           0      0          0         0       0     0      0      0
#> 1        3           0      3          0         1       0     0      0      0
#> 7        8           0      9          0         0       0     0      0      0
#> 37       0           0      0          0         0       1     0      0      0
#> 38       1           0      0          0         0       0     0      0      0
#> 47       3           0      3          0         3       3     0      0      0
#> 24       7           0      0          9         4       6     0      0      0
#> 46       3           1     14          2         9      16     0      0      0
#> 43      44           0     32          0        13      25     0      0      0
#> 45       1           0      4          0         2       4     0      0      0
#> 50       0           0      1          0         3      59     0      0      0
#> 40       0           0      0          0         1       0     0      0      0
#> 42       3           0      0          0         5       1     0      0      0
#> 14      15           0     34          0        20       1     0      0      0
#> 49      14           0     31          2        19       4     0      0      0
#> 51       4           0     19          0         2       0     0      0      0
#> 29       4           0     27          0         2       0     0      0      0
#> 30       9           0     23          0       144       3     0      0      0
#> 31       8           0     26          0        27       2     4      0      0
#> 33       0           0      6          0         3       0     0      0      0
#> 6        1           0      2          0         4       2     0      0      0
#> 41       1           0      3          0        12       0     0      0      0
#> 26       2           0      0          0         0       1     0      0      0
#> 27       3           0      2          0         1       0     0      0      0
#> 34       3           1      9          0         0       1     0      0      0
#> 35      13           0     18          0         5       0     0      0      0
#> 10       0           0      9          0        16       0     0      0      0
#> 15       0           0      9          0         2       0     0      0      0
#> 16       0           0     17          0        19       4     0      0      0
#> 17       0           0      5          0        17       2     0      0      0
#> 18       9          11    117          1        62       9    15      0      0
#> 19       1           0     19          0         4       0     0      0      0
#> 20       0           0      0          1       182       0     0      0      0
#> 21       0           0      2          0         0       0     0      0      0
#> 22      10           0      3          0        49       0     0      0      0
#> 25       0           1      0          0         1       0     0      4      0
#> 28      12           0    175         19         7      55   263      0      0
#> 32       0           0      1          0         0       0     0      0      1
#> 36      21           2     39          0        24       7    16      0      0
#> 48       7           0      0          5        33       0     0      0      0
#> 13       1           0      5          0         3       1     0      0      0
#> 12       2           0     24          0         6       3     0      0      0
#> 11       0           0      0          0         0       0     0      0      0
#> 23      25           0      2          0         2       7     1      0      1
#> 39       0           0      0          0         0       0     0      0      0
#> 44       0           0      3          0        19       0     0      0      0
#>    Curcu1 Curcu2 Diame1 Diame2 Dimec Dytis1 Ephyd2 Geran Helicho Hemer1 Hyale
#> 2       0      0      1      0     0      0      0     0       0      2     0
#> 3       0      0      0      0     0      0      0     0       0      0     0
#> 4       0      0      2      1     0      0      0     0       0      1     0
#> 5       0      0      0      0     0      0      0     0       0      0     0
#> 8       0      0      0      0     0      1      0     0       0      0     0
#> 9       0      0      1      0     0      0      0     0       0      0     0
#> 1       0      0      0      0     0      0      0     0       0      0     0
#> 7       0      0      0      0     0      0      0     0       0      1     0
#> 37      0      0      0      0     0      0      0     0       0      0     1
#> 38      1      0      2      0     0      0      0     0       0      0     0
#> 47      0      0      0      0     0      0      0     0       0      0     2
#> 24      0      0      1      1     2      0      0     0       0      0    39
#> 46      0      0      0      0     0      0      0     0       0      0     9
#> 43      0      0     16      8     1      0      0     0       0      0    14
#> 45      0      0      3      4     0      0      0     1       0      0    65
#> 50      0      0      0      0     0      0      0     0       0      0    11
#> 40      0      0      0      0     0      0      0     0       0      0   103
#> 42      1      0      3      5     0      0      0     0       0      0    18
#> 14      0      0     24     10     0      0      0     0       0      1    36
#> 49      0      0     28      6     0      0      0     0       0      0    32
#> 51      0      0      0      2     0      0      0     0       0      0    45
#> 29      0      0     21      6     0      0      0     0       0      0     9
#> 30      0      0     59     16     0      0      0     0       0      4   166
#> 31      0      0    131     43     0      0      0     0       0      0    32
#> 33      0      0     56     20     0      0      0     0       0      1     9
#> 6       0      0      0      0     0      0      0     0       0      0     0
#> 41      0      0      1      5     0      0      0     0       0      0    32
#> 26      0      0      0      0     0      0      0     0       0      0    41
#> 27      0      0      6      2     0      0      0     2       0      0   245
#> 34      0      0      2      2     0      0      0     0       0      0    18
#> 35      0      0    239    143     0      0      0     0       1      0     3
#> 10      0      0      0      0     0      0      0     0       1      0    20
#> 15      0      0     28      9     0      0      0     0       0      4   219
#> 16      0      0     33     11     0      0      0     0      11      1  1867
#> 17      0      0      1      0     0      0      0     0       0      0   418
#> 18      1      0    168     41     0      0      0     0       0      0    19
#> 19      0      0      1      0     1      0      0     0       0      0    23
#> 20      0      0      0      1     0      0      0     1       0      0  1871
#> 21      0      0      1      0     0      0      0     0       0      0  3230
#> 22      0      0      7      1     1      0      0     0       0      0   389
#> 25      0      0      0      0     0      0      0     1       0      0  1548
#> 28      0      0     14    133     0      0      0     2       5      0    73
#> 32      0      0      1      0     0      0      0     0       0      0     5
#> 36      1      0     61     18     0      0      0     0       0      0    12
#> 48      0      1      0      0     0      0      0     3       0      5   474
#> 13      0      0      1      1     0      0      0     1       0      0   350
#> 12      0      0      0      0     0      0      0     0       0      0   149
#> 11      0      0      0      3     3      0      1     0       0      4   906
#> 23      0      0      3      0     0      0      0     0       0      0   648
#> 39      0      0      0      0     0      0      0     0       0      0   290
#> 44      0      0      0      0     0      0      0     0       0      0  1621
#>    HYDRA Hydrosc Leech1 Leech2 Leech3 Leech4 Leuco Limoniindet Lumbri Lymnae
#> 2      0       0      0      0      0      0     0           0      0      0
#> 3      0       0      0      0      0      0     0           0      0      0
#> 4      0       0      0      0      2      0     0           0      0      0
#> 5      0       0      0      0      0      0     0           0      0      0
#> 8      0       0      0      0      0      0     0           0      0      0
#> 9      0       0      0      0      0      0     0           0      0      0
#> 1      0       0      0      0      2      0     0           0      0      0
#> 7      0       0      0      0      0      0     0           0      0      0
#> 37     0       0      0      0      0      0     0           0      1      0
#> 38     0       0      0      0      0      0     0           0      6      0
#> 47    15       0      0      0      0      0     0           0    167      0
#> 24    16       0      1      0      0      0     0           0      3      0
#> 46    19       0      1      0      0      0     0           0    133      0
#> 43     6       0      0      0      0      0     0           0     24      0
#> 45    11       1      0      0      0      0     0           0     60      0
#> 50     5       0      0      0      0      0     0           0    104      0
#> 40     0       0      1      0      1      0     0           0      4      0
#> 42     2       0      0      0      0      0     0           0      2      0
#> 14    12       0      1      0      0      0     0           0      5      0
#> 49    22       0      0      0      0      0     0           0      6      0
#> 51    25       0     10      0      0      0     0           0     33      0
#> 29    15       0      2      0      0      0     0           0      0      0
#> 30     3       0      3      1      2      0     0           0      3      0
#> 31     5       0      2      0      0      0     0           0     18      0
#> 33     2       0      0      1      0      0     0           0      9      0
#> 6      0       0     22      0      0      0     0           0      0      0
#> 41     5       0      1      0      0      0     0           0      1      0
#> 26     3       0      0      0      0      4     0           0     12      0
#> 27     7       0      2      0      0      0     0           0      4      0
#> 34     8       0      0      0      0      0     0           0      1      0
#> 35     5       0      0      0      0      0     0           0      7      0
#> 10     1       0      0      0      0      0     0           0     56      0
#> 15     6       0      5      0      0      0     0           0      8      0
#> 16    37       0      2      0      0      0     0           0     19      0
#> 17     6       0     10      1      0      0     0           0    239      1
#> 18    36       0      4      0      0      0     0           0      7      0
#> 19     4       0     12      2      0      0     0           0      1      0
#> 20    41       0      1      0      4      0     0           0     19      1
#> 21   480       0      2      0      0      0     0           4      2      0
#> 22     5       0      0      0      0      0     0           0      1      0
#> 25    29       0     36      1      0      0     1           0     46      1
#> 28     3       1      0      0      0      0     0           0      7      0
#> 32     1       0      1      0      0      0     0           0    188      0
#> 36    18       0      0      0      0      0     0           0      3      0
#> 48    21       0     42      6      0      0     0           0     74      0
#> 13     4       0      1      0      0      0     0           0      6      0
#> 12    23       0      0      0      0      0     0           0      8      0
#> 11     7       0      3      3     35      0     0           0     57      0
#> 23     5       0      4      0      0      0     0           0     23      0
#> 39     1       0     26     10      0      0     0           0     54      0
#> 44    60       0      0      1      0      0     0           0      5      0
#>    Maya Molo1 Molo2 Morto Musci5 Musci6 Musci7 Musci4 Musci1 Musci2 Musci3
#> 2     0     1     0     0      0      0      0      1     11      0      0
#> 3     0     0     0     0      0      0      0      0      0      0      0
#> 4     0     0     0     0      0      0      0      0      8      0      0
#> 5     0     0     0     0      0      0      0      1      0      0      0
#> 8     0     0     1     0      0      0      0      0      2      0      0
#> 9     0     0     0     0      0      0      0      0      0      0      0
#> 1     0     0     1     0      0      0      0      0      0      0      0
#> 7     0     0     0     0      0      0      0      0      0      0      0
#> 37    0     0     0     0      0      0      0      0      0      0      0
#> 38    0     1     0     0      0      0      0      0      0      0      0
#> 47    0     0     0     0      0      0      0      0      2      0      0
#> 24    0    11     0     1      0      0      0      3      2      0      0
#> 46    0     2     0     0      0      0      0      0      1      0      0
#> 43    0   120     0     0      0      0      0      0      6      3      7
#> 45    0    26     0     2      0      0      1      0      0      1      0
#> 50    0    24     5     5      0      0      0      0      0      0      0
#> 40    0     1     0     1      0      0      0      0      0      0      0
#> 42    0     3     0    12      0      0      0      0      1      0      0
#> 14    0     7     0   277      0      0      0      0      1      0      0
#> 49    0     1     0    14      0      0      0      0      1      0      0
#> 51    0    10     0    28      0      0      0      0      0      0      0
#> 29    0     2     0    54      0      0      0      0      0      0      0
#> 30    0    20     0     8      0      0      0      0      0      0      1
#> 31    0     9     0     4      0      0      1      0      0      0      0
#> 33    0    15     0     4      0      0      0      0      0      0      0
#> 6     0     0     0     0      0      0      0      0      0      0      0
#> 41    2     7     0    83      0      0      0      0      0      0      0
#> 26    0     7     0     0      0      0      0      0      0      0      0
#> 27    0    16     0     0      0      0      0      1      0      0      0
#> 34    0    14     0    45      0      0      0      0      1      0      0
#> 35    0     3     0     5      0      0      0      0      0      0      0
#> 10    0     2     0    30      0      0      0      0      2      0      0
#> 15    0    10     0     0      0      0      0      0      2      0      0
#> 16    0    20     0     0      0      0      0      0      2      0      0
#> 17    0    24     0     0      0      0      0      0      3      0      0
#> 18    0     8     0     1      0      0      0      0      0      0      0
#> 19    0    19     0     0      0      0      0      0      0      0      0
#> 20    0     0     0     0      0      0      0      0      0      0      0
#> 21    0     0     0     0      0      0      0      1     15      0      0
#> 22    0     4     0     2      0      0      0      1      0      0      0
#> 25    0     0     0     0      0      0      0      0      0      0      0
#> 28    0    22     0    88      0      0      0      0      0      0      0
#> 32    0     1     0     0      0      0      0      0      0      0      0
#> 36    0    11     0     0      0      0      0      0      0      0      0
#> 48    0     0     0     0      0      0      0      0      0      0      0
#> 13    0    10     0    14      0      0      0      0      3      3      2
#> 12    0     0     0     0      0      0      0      0      0      0      0
#> 11    0     0     0     0      1      3      0      3     18      0      0
#> 23    0    11     0    95      0      0      0      0     15      0      2
#> 39    0     1     0     0      0      0      0      0      7      0      0
#> 44    0     1     0     2      0      0      0      0      0      0      2
#>    Naid1 Naid2 Naid3 Nectop Nema Neoel1 Neoel2 Neot Nepti Nona1 Ochro Ortho
#> 2     39     0     0      0    2      0      0    0     0     0     0    72
#> 3      0     0     0      0    0      0      0    0     0     0     0     0
#> 4     32     0     0      0    4      0      1    0     0     0     0    85
#> 5      0     0     0      0    0      0      0    0     0     0     0     7
#> 8      0     0     0      0    2      0      0    0     0     0     0    43
#> 9      0     0     0      0    0      0      0    0     0     0     0     2
#> 1     19     0     0      0   16      0      0    0     0     0     0   109
#> 7      9     0     0      0   29      1      5    0     0     0     4   111
#> 37     0     0     0      0    1     87      2    0     0     0     0     3
#> 38     0     0     0      0    1      7      1    0     0     0     1     1
#> 47     0     0     0      0    0     27      5   13     0     0     0    97
#> 24     0     1     0      2    1    301     16    0     2     1     0    36
#> 46     0     0     0      1    0     52     12    7     0     0     0   306
#> 43    10     2     0      3    1     34      2    1     0     0     0   746
#> 45     2     0     0      0    2     14      1   14     0     0     0   273
#> 50     2     0     0      2    2    122     13    0     0     0     0   190
#> 40     1     0     0      0    0     23      3    4     0     0     0     5
#> 42     0     0     0      0    1     26      5    2     0     0     5    66
#> 14     0     0     0      1   11     43      8    0     0     0     3   605
#> 49     2     0     0      0    2     17      0    0     0     0    81   353
#> 51    22    26     0      0    0     19     11   12     0     0    60   708
#> 29     3     0     0      0    2      3      0    0     0     0     3   579
#> 30     8     0     0      0    2      5      2    2     0     1     0  1920
#> 31     8     0     0      0    7      6      1    4     0     0     0  2372
#> 33     2     0     0      0   29      3      3    1     0     0     0  2330
#> 6     37     0     0      0    2     18     30    0     0     0    19   414
#> 41     2     0     0      0    0     46      7    7     0     0    12    90
#> 26     0     0     0      0    1     23      0    0     0     0     1   182
#> 27     0     0     0      0    2    157      0    0     0     0     0   228
#> 34     0     0     0      0    0     98      2    1     0     0     0  1442
#> 35     0     0     0      0    1     17      0    3     3     0     0  9237
#> 10     0     0     0      0   20      1      0    0     0     0     0   189
#> 15    29     0     0      0    8    138     21    0     1     0    31   629
#> 16     2    10     0      0    3      7      0    0     0     0    80  1618
#> 17    15     0     0      0    4      1      0    0     0     0     1   466
#> 18     0     0     0      0    4     23      1  109     0     0     3  2922
#> 19     0     1     0      0    0    145      1    0     0     0     0   626
#> 20     3    16     0      0    4     43      0    0     0     0     0   503
#> 21     0     0     0      0    3      6      0    0     0     0     0    49
#> 22     2     0     0      1    0     27      0    0     0     0     1   338
#> 25    13     0     0      0    9      0      0    0     0     0     0   531
#> 28     1     3     0     10    0     35      7  144     0     0    10   961
#> 32     7     0     0      0    1      0      0    0     0     0     0    21
#> 36     2     0     0      0    9    174     12    8     0     0     0  2332
#> 48     5     0     0      0    5     19      0    1     0     0     0   519
#> 13     2     0     0      0    2      7      1    0     0     0    18   704
#> 12     5     0     0      0    2      1      0    0     0     0     7   540
#> 11    49    10    12      0    1      3      1    0     0     0     0   848
#> 23     7     0     0      0    0     53     11    0     0     0     0   520
#> 39     8     0     0      0    1     11      1    0     0     0     0     7
#> 44     0     4     0      0    0     15      0    0     0     0     0   230
#>    Ostra Podo1 Podo2 Podo3 Podo4 Priono1 Priono2 Priono3 Schoe Simu1 Sphae
#> 2      0    24     0     4     1       0       0       0     0   124     0
#> 3      0    16     0    28     0       0       0       0     0     0     0
#> 4      0   177     0     2     2       0       0       0     0    18     0
#> 5      0    13     0    71     1       0       0       0     0     0     0
#> 8      0    46     0     3     0       0       0       0     0     3     0
#> 9      0    49     0    20    14       0       0       0     0     0     0
#> 1      0    20     0     1     5       0       0       0     0     9     0
#> 7      0     3     0     1     0       2       0       0     0    21     0
#> 37     0     0     0     0     0       0       0       0     0     4     0
#> 38     2     0     0     2     0       0       0       0     0    15     0
#> 47     0     7     0    27     0       7       0       0     0    60     0
#> 24    52    15     1    19     0      61       8       0     0    67     0
#> 46     2     8     0     4     0       5       0       0     0    49     1
#> 43     0    55     0   176     8       8       4       0     0    79     0
#> 45     2    26     0    34     0      19       2       0     0    29     0
#> 50     0   151     0   521     0      22       3       2     0   101     0
#> 40     0     0     0     0     0       4       1       0     0     3     0
#> 42     0     0     0     0     0       2       0       0     0     2     0
#> 14     0    12     0    10     0       5       0       0     0    20     3
#> 49     5     7     0     8     0       0       0       0     0    24     2
#> 51     3     9     0     6     0       4      12       0     0    18     0
#> 29     1     6     0     1     0       0       0       0     1     5     0
#> 30     4     2     0    24     0       2       0       0     0     3     2
#> 31     1     1     0    13     0       1       0       0     1     3     0
#> 33     0     0     0     3     0       1       0       0     0     4     0
#> 6      0    37     0    18     2       4       0       0     0    11     0
#> 41     2     1     0     0     0       0       0       0     0     0     0
#> 26   126     1     0     1     0      37       2       0     0   127     0
#> 27    17     7     0     0     0      16       0       0     0    11     0
#> 34     0     1     1    51     0      11       1       0     0    20     0
#> 35     0     8     0     9     0      15       0       0     0    11     0
#> 10     0     0     0    10     0       0       0       0     0    31     0
#> 15     0     4     0     0     0       3       0       0     0    12     0
#> 16     0     0     0     2     0       8       0       0     0    22     0
#> 17     6     1     0     0     0       0       0       0     0    26     7
#> 18    30     1     0     1     0     168       4       0     0    21     0
#> 19     5     1     0    26     0      66       2       0     0   168     0
#> 20    17     2     0     1     0       1       0       0     0   167     0
#> 21     1   243     0     0     0       0       0       0     0     0     0
#> 22     5     2     0     4     0      22       3       0     0    23     1
#> 25  1804     0     0     0     0       1       0       0     0   148     2
#> 28     2     0     0    60     0      16       0       0     0    13     0
#> 32     1     0     0     0     0       0       0       0     0     1     0
#> 36     4     1     0     7     0      69      14       0     0   131     0
#> 48    96     1     2     0     0      12       0       0     0    13     0
#> 13     0     1     0     3     0       1       0       0     0    76     2
#> 12     0     0     0     0     0       0       0       0     0     0     0
#> 11    76     3     0     0     0       0       0       0     0     0    21
#> 23     4    10     0     8     0       9       1       0     0     5     3
#> 39    19     0     0     0     0       3       0       0     0     0    12
#> 44    29    30     0     8     0       4       0       0     0    26     3
#>    Staphy1 Staphy2 Stilo1 Sync1 Tanyp Tipu Trichoco
#> 2        1       0      0     0     0    0        0
#> 3        0       0      0     0     0    0        0
#> 4        0       0      0     0     0    0        0
#> 5        0       0      0     0     0    0        0
#> 8        0       0      0     0     0    0        0
#> 9        1       0      0     0     0    0        0
#> 1        0       1      0     0     0    1        0
#> 7        0       0      0     0     0    0        0
#> 37       0       0      0     0     0    0        0
#> 38       0       0      0     0     0    0        0
#> 47       0       0      0     0     0    0        0
#> 24       0       0      0     0     0    0        0
#> 46       0       0      0     0     3    0        0
#> 43       0       0      0     0    17    0        0
#> 45       0       0      0     0     2    0        0
#> 50       0       0      0     0     4    0        0
#> 40       0       0      0     0     0    0        0
#> 42       0       0      0     0     0    0        0
#> 14       0       0      0     1    22    0        0
#> 49       0       0      1     1     0    0        0
#> 51       0       0      0     0     8    0        0
#> 29       0       0      0     0     3    0        0
#> 30       0       0      0     0    13    0        0
#> 31       0       0      0     0     4    0        0
#> 33       0       0      0     0     1    0        0
#> 6        0       0      0     0     1    0        0
#> 41       0       0      0     0     0    0        0
#> 26       0       0      0     0     3    0        0
#> 27       0       0      0     0    11    0        0
#> 34       0       0      0     0    14    0        0
#> 35       0       0      0     3    68    0        0
#> 10       0       0      0     0     7    0        0
#> 15       0       0      0     0    16    0        0
#> 16       0       0      0     0    16    0        0
#> 17       0       0      0     0     2    0        0
#> 18       0       0      0     0     7    0        0
#> 19       0       0      0     0     2    0        0
#> 20       0       0      0     0   130    0        0
#> 21       0       0      0     0     0    0        4
#> 22       0       0      0     0     0    0        0
#> 25       0       0      0     0     0    0        2
#> 28       0       0      2     1   241    0        0
#> 32       0       0      0     0     0    0        0
#> 36       0       0     10     0     8    0        0
#> 48       0       0      0     0    44    0        0
#> 13       0       0      0     2     5    0        0
#> 12       0       0      0     0     0    0        0
#> 11       0       0      0     0     1    0        0
#> 23       0       0      0     0     0    0        0
#> 39       0       0      0     0     0    0        0
#> 44       0       0      0     0     2    0        0

^{Created on 2020-03-24 by the reprex package (v0.3.0)}

andresrcs · March 24, 2020, 9:37pm

That is not copy/paste friendly, please read the guide I gave you before and post a proper reproducible example.

riokoto80 · March 24, 2020, 9:38pm

Super, here is the link to the file:

Thank you very much for your help @andresrcs

andresrcs · March 24, 2020, 9:48pm

I still can't reproduce, I get the expected results, maybe your problem is the way you are reading the data.

url <- "https://www.dropbox.com/s/uv3a9yutfxmc8oz/MBC_SPP_ALL.csv?dl=1"
spe <- read.csv(url)
rowSums(spe[,-1])
#>  [1]   287    44   340    93   107    87   214   268   112    58   809  1654
#> [13]  1233  2686   994  2783   226   363  1510  1497  1461  1028  2969  2823
#> [25]  2595   760   645  2076  1285  2126 10050   534  1694  4202  1379  4135
#> [37]  1407  3855  4049  1664  4395  3091   232  3367  1458  1732  2400  2116
#> [49]  1833   555  2797
rowSums(spe[,-1] > 0)
#>  [1] 16  2 15  5  9  6 17 17 10 15 20 34 28 35 32 28 21 26 33 30 31 27 36 35 26
#> [26] 20 25 23 25 30 27 19 26 27 25 34 26 25 17 28 22 37 14 32 26 34 16 28 31 18
#> [51] 22

riokoto80 · March 24, 2020, 10:22pm

Oh Yes, the problem then might be the way I was reading the data, or maybe the functions that I was using? I don’t think that’s the case, but, any way, thanks a lot for your help and time
When I read the file from my files as:
spe<-(read.table("~/Dropbox/Docs Redro/Paper Tesis MBC/MBC_SPP_ALL.csv", sep=",", header=TRUE, row.names=1))
I still get the same mistakes on my sums and counts, but when I read it like you did url <- "https://www.dropbox.com/s/uv3a9yutfxmc8oz/MBC_SPP_ALL.csv?dl=1"
spe <- read.csv(url)
I get the expected results as from excel counts and sums, kind of strange.

andresrcs · March 24, 2020, 10:33pm

When you read this way you don't get the row names on the first column so there is no need to exclude the first column (spe[,-1])

riokoto80 · March 24, 2020, 11:01pm

Ah, ok, still a lot to learn in R.
Thank you a lot @andresrcs

system · April 14, 2020, 11:01pm

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