gistfile1.txt

arc<-as.data.frame(arc)
arcraw<-as.data.frame(arcraw)
varPlot(form=rochefant~(region), Data=arc)
varPlot(form=rochefant~(customer), Data=arc) # some customers for sure provided more data then others 
varPlot(form=rochefant~(locality), Data=arc)
varPlot(form=rochefant~(slaughteryear), Data=arc)
varPlot(rochefant~(slaughteryear+slaughtermonth), arc, keep.order = FALSE,
        MeanLine=list(var=c("int", "slaughteryear"), 
                      col=c("magenta", "blue"), lwd=c(2,2)))
varPlot(form=rochefant~(strain), Data=arc)
varPlot(form=rochefant~(weightclasshalv), Data=arc) # relationship between weight and pigmentation is not THAT direct
ggplot(data      = arc,
       aes(x     = rochefant,
           y     = nirfat,
           col   = as.numeric(customer),
           group = as.numeric(customer)))+ #to add the colours for different classes
  geom_point(size     = 1.2,alpha    = .8,position = "jitter")+ #to add some random noise for plotting purposes
  theme_minimal()+theme(legend.position = "none")+
  scale_color_gradientn(colours = rainbow(100))+
  geom_smooth(method = lm, se = FALSE,size = .5, alpha  = .8) + # to add regression line
  labs(title    = "Pigmentation & NirFat",
       subtitle = "add colours for different customers and regression lines")

ggplot(data      = arc,
       aes(x     = rochefant,
           y     = nirfat,
           col   = as.factor(weightclasshalv))) +
  geom_point(size= 1.2, alpha = .8, position = "jitter") + #to add some random noise for plotting purposes
  theme_minimal() + theme(legend.position = "none") +
  geom_smooth(method = lm, se = FALSE,size = .5, alpha  = .8) 

ggplot(data      = arc,
       aes(x     = rochefant,
           y     = nirfat,
           col   = as.factor(slaughtermonth))) +
  geom_point(size= 1.2, alpha = .3, position = "jitter") + #to add some random noise for plotting purposes
  theme_minimal() + theme(legend.position = "none") +
  geom_smooth(method = lm, se = FALSE,size = .5, alpha  = .8)

ggplot(data      = arc,
       aes(x     = rochefant,
           y     = nirfat,
           col   = as.factor(strain))) +
  geom_point(size= 1.2, alpha = .3, position = "jitter") + #to add some random noise for plotting purposes
  theme_minimal() + theme(legend.position = "none") +
  geom_smooth(method = lm, se = FALSE,size = .5, alpha  = .8)

ggplot(data      = arc,
       aes(x     = rochefant,
           y     = `nir-ala`,
           col   = as.numeric(customer),
           group = as.numeric(customer)))+
  geom_point(size     = 1.2,alpha    = .8,position = "jitter")+
  theme_minimal()+theme(legend.position = "none")+
  scale_color_gradientn(colours = rainbow(100))+
  geom_smooth(method = lm, se = FALSE,size = .5, alpha  = .8) 

ggplot(data      = arc,
       aes(x     = rochefant,
           y     = arc$`nir-dha`,
           col   = as.numeric(customer),
           group = as.numeric(customer)))+
  geom_point(size     = 1.2,alpha    = .8,position = "jitter")+
  theme_minimal()+theme(legend.position = "none")+
  scale_color_gradientn(colours = rainbow(100))+
  geom_smooth(method = lm, se = FALSE,size = .5, alpha  = .8)