diff --git a/IMPLAN_Visuals.r b/IMPLAN_Visuals.r
index a5df976..4401858 100644
--- a/IMPLAN_Visuals.r
+++ b/IMPLAN_Visuals.r
@@ -12,10 +12,19 @@ return(DATA)
 }
 
 DATA <- GET_DATA()
+TEMP <- DATA %>% filter(year==2035)
+TEMP <- DATA %>% filter(year==2035)
+RES <- TEMP %>% mutate(year=2036)
+for(i in 2037:2060){
+RES <- RES %>% rbind(TEMP %>% mutate(year=i))
+}
+DATA <- DATA %>% rbind(RES)
+DATA$Type <-  factor(DATA$Type,levels=c("Direct","Indirect","Induced"))
+DATA
 EMP_WY <- DATA %>% filter(Impact=="Employment",Region=="WY")
 DOL_WY <- DATA %>% filter(Impact!="Employment",Region=="WY")
-
-ggplot(EMP_WY, aes(x = year, y = value, fill = Type)) +  geom_bar(stat = "identity", position = "stack") +  theme_minimal()
+ggplot(EMP_WY, aes(x = year, y = value, fill = Type)) +  geom_area(stat = "identity", position = "stack") +  theme_bw()+scale_x_continuous(breaks=2026:2060)+scale_y_continuous(breaks=seq(0,10000,by=250))+ylab("Wyoming Employment Additions\n(Full-time Equivalent)")
+																	    ?scale_y_continuous
 ggplot(DOL_WY, aes(x = year, y = value/10^9, fill = Type)) +  geom_bar(stat = "identity", position = "stack") +  theme_minimal()+facet_wrap(~Impact)