Hi,
I have created a PCA plot with ggfortify and plotly. On this PCA there are different species of bees visualised as loadings. Also the plots and their dominant tree species are visualised with colours ('Boomtype'). lastly 3 variabels of the plots are visualised as loadings on the PCA (authenticiteit=authenticity; totale_abundantie=total abundance; and Aantal bloemen=number of flowers).
My question now is: how do i seperate the different loadings of bee species from the 3 variabels so it is visible on 2 different graphs, but still using all data? There are also a lot of bee species with only 1 observation and this makes the graph messy and want to only visualize the most important species.
here is an example of how I want it:
My R code:
Bijen_df <- as.data.frame(PCA_Bijen) # eerst moet de tibble omgevormd worden naar een dataframe.
rownames(Bijen_df) <- c("B21","B22","B31","B32","B41","B42","B51","B52","B61","B62","B81","B82","B91","B92","O31","O32","O41","O42","O51","O52","O61","O62","O71","O72","P11","P12","P21","P22","P31","P32","P51","P52","P61","P62","P71","P72","P81","P82")
#Dan moet de eerste rij van plot verwijdert worden. en de andere rijen die geen bij zijn
PCA_Bijen_df <- Bijen_df %>% select(-Plot, -Boomtype)
PCA_Bijen_df
#dan wordt de data log getransformeerd.
PCA_Bijen_log <- log(PCA_Bijen_df+1) # we doen plus 1 want anders krijgen we '-inf' values en werkt de ggfortify niet.
PCA_Bijen2 <- prcomp(PCA_Bijen_log, scale. = TRUE)
p <- autoplot(PCA_Bijen2, data = Bijen_df, colour = "Boomtype",
shape = FALSE, label = TRUE, label.size = 3,
loadings = TRUE, loadings.colour = "black", loadings.label = TRUE, loadings.label.size = 3, loadings.label.colour = "black", frame = TRUE)+ theme_bw(base_size = 12)
ggplotly(p)
My data:
| Plot |
Andrena_angustior |
Andrena_bicolor |
Andrena_cineraria |
Andrena_clarkella |
Andrena_dorsata |
Andrena_fulva |
Andrena_gravida |
Andrena_haemorrhoa |
Andrena_helvola |
Andrena_mitis |
Andrena_nitida |
Andrena_scotica |
Andrena_spec. |
Anthrophora_plumipes |
Apis_mellifera |
Bombus campestris |
Bombus hypnorum |
Bombus_lapidarius |
Bombus_lucorum |
Bombus_pascuorum |
Bombus_pratorum |
Bombus_terrestris |
Bombus_vestalis |
Bombus_spec. |
Halictus_tumulorum |
Halictus_scabiosae |
Lasioglossum_calceatum |
Lasioglossum_malachurum |
Lasioglossum_morio |
Lasioglossum_parvulum |
Lasioglossum_spec. |
Micrandrena_spec. |
Nomada_fabriciana |
Nomada_ferruginata |
Nomada_flava |
Nomada_flavoguttata |
Nomada_goodeniana |
Nomada_leucophthalma |
Nomada_panzeri |
Nomada_ruficornis |
Nomada_zonata |
Boomtype |
Authenticiteit |
Totale_abundantie |
Aantal_bloemen |
| B21 |
1 |
0 |
0 |
0 |
0 |
2 |
0 |
7 |
8 |
1 |
0 |
3 |
0 |
0 |
5 |
0 |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
0 |
0 |
B |
0.18 |
100 |
127 |
| B22 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
4 |
7 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
1 |
1 |
1 |
0 |
1 |
0 |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
B |
0.18 |
107 |
120 |
| B31 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
B |
0.2 |
100 |
35 |
| B32 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
B |
0.2 |
110 |
135 |
| B41 |
0 |
0 |
0 |
0 |
1 |
1 |
0 |
3 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
B |
0.31 |
100 |
7 |
| B42 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
3 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
B |
0.31 |
115 |
44 |
| B51 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
B |
0.56 |
100 |
270 |
| B52 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
B |
0.56 |
100 |
603 |
| B61 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
7 |
5 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
B |
0.3 |
105 |
14 |
| B62 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
B |
0.3 |
130 |
7 |
| B81 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
16 |
3 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
2 |
0 |
3 |
0 |
0 |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
B |
0.36 |
110 |
138 |
| B82 |
0 |
0 |
1 |
0 |
0 |
0 |
1 |
3 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
B |
0.36 |
100 |
0 |
| B91 |
0 |
0 |
0 |
0 |
1 |
2 |
0 |
2 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
0 |
0 |
B |
0.53 |
90 |
85 |
| B92 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
7 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
B |
0.53 |
100 |
466 |
| O31 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
2 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
O |
0.39 |
95 |
15 |
| O32 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
O |
0.39 |
100 |
37 |
| O41 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
11 |
2 |
0 |
0 |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
O |
0.41 |
135 |
207 |
| O42 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
9 |
1 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
O |
0.41 |
90 |
240 |
| O51 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
3 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
O |
0.25 |
130 |
35 |
| O52 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
O |
0.25 |
140 |
177 |
| O61 |
2 |
0 |
0 |
0 |
0 |
0 |
0 |
10 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
O |
0.23 |
110 |
170 |
| O62 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
1 |
O |
0.23 |
105 |
282 |
| O71 |
0 |
1 |
0 |
0 |
0 |
0 |
1 |
3 |
1 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
0 |
3 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
O |
0.47 |
60 |
75 |
| O72 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
1 |
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 |
0 |
1 |
0 |
0 |
O |
0.47 |
95 |
35 |
| P11 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.44 |
150 |
793 |
| P12 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
0 |
0 |
0 |
3 |
1 |
0 |
P |
0.44 |
115 |
398 |
| P21 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
0 |
1 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
P |
0.69 |
105 |
551 |
| P22 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.69 |
130 |
426 |
| P31 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.64 |
125 |
512 |
| P32 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
2 |
1 |
0 |
P |
0.64 |
110 |
29 |
| P51 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
12 |
5 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.55 |
70 |
927 |
| P52 |
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 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.55 |
95 |
639 |
| P61 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.35 |
90 |
322 |
| P62 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.35 |
125 |
14 |
| P71 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.26 |
80 |
366 |
| P72 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.26 |
110 |
336 |
| P81 |
1 |
0 |
0 |
1 |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.48 |
120 |
182 |
| P82 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
P |
0.48 |
110 |
327 |