# Problem 3 #
dat3 = read.csv("http://course1.winona.edu/bdeppa/DSCI%20415/Data/Dune%20with%20Environmentals.csv")
attach(dat3)

install.packages("tidyr")
library(vegan)
library(proxy)
library(dplyr)
library(tidyr)
library(MASS)

names(dat3)
dim(dat3)

spec.mat = dat3 %>% select(Achimill:Callcusp)

rowS = rowSums(spec.mat)
spec.count = colSums(spec.mat)

site.dist = dist(spec.mat,method="Bray")
site.iso = isoMDS(site.dist,k=2)
plot(site.iso$points,type = "n")
text(site.iso$points,as.character(Site),col=as.numeric(Moisture)+1) #not sure about moisture

colSums(spec.mat)

##how can we make bubble for different managment sites or use
tspec.mat = t(spec.mat)
spec.dist = dist(tspec.mat,method = "Bray")
spec.iso = isoMDS(spec.dist,k=2)
plot(spec.iso$points,type="n")
text(spec.iso$points,as.character(row.names(tspec.mat)),col=as.numeric(Moisture)+1,cex=.7)

##tried to do bubbles, gave up, gg rip
install.packages("plotly")
library(plotly)
p <- plot_ly(dat3, x = spec.iso$points[,1], y = spec.iso$points[,2], text = as.character(row.names(tspec.mat)),col=as.numeric(dat3$Moisture), type = 'scatter', mode = 'markers',
             marker = list(size = as.numeric(dat3$Management)*5, opacity = 0.5)) %>%
  layout(title = 'Gender Gap in Earnings per University',
         xaxis = list(showgrid = FALSE),
         yaxis = list(showgrid = FALSE))
p

detach(dat3)