gistfile1.txt

g1<-ggplot(total[!total$Patientnr==8, ], 
           aes(x=SurvTimeWeek))+  geom_density(color="darkblue", fill="lightblue")+theme_bw()
g2<-ggplot(total[!total$Patientnr==8, ], 
           aes(x=SurvTimeWeek, fill=Performance_status_at_consultation))+
  geom_density(alpha=0.5)+theme_bw()
g3<-ggplot(total[!total$Patientnr==8, ],aes(x=SurvTimeWeek, fill=Gender))+
  geom_density(alpha=0.5)+theme_bw()
g4<-ggplot(total[!total$Patientnr==8, ],aes(x=SurvTimeWeek, fill=Disease_stage_at_consultation))+
  geom_density(alpha=0.5)+theme_bw()
g5<-ggplot(total[!total$Patientnr==8, ], 
           aes(x=SurvTimeWeek, fill=Surgery_prior_to_consultation))+
  geom_density(alpha=0.5)+theme_bw()
g6<-ggplot(total[!total$Patientnr==8, ], 
           aes(x=SurvTimeWeek, fill=Chemotherapy_prior_to_consultation))+
  geom_density(alpha=0.5)+theme_bw()
g7<-ggplot(total[!total$Patientnr==8, ], 
           aes(x=SurvTimeWeek, fill=as.factor(Opioid_YN)))+
  geom_density(alpha=0.5)+theme_bw()
g8<-ggplot(total[!total$Patientnr==8, ], 
           aes(x=SurvTimeWeek, fill=Non_opioid_spec))+
  geom_density(alpha=0.5)+theme_bw()
g9<-ggplot(total[!total$Patientnr==8, ], 
           aes(x=SurvTimeWeek, fill=Tumorsite_in_pancreas))+
  geom_density(alpha=0.5)+theme_bw()
g10<-ggplot(pancreas[!pancreas$Patientnr==8, ], 
            aes(x=SurvTimeWeek, fill=Opioid_spec))+
  geom_density(alpha=0.5)+theme_bw()
grid.arrange(g1,g2,g3,g4,g5,g6,g7,g8,g9,g10)