Added minor line to show averages for paper
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@ -98,6 +98,9 @@ IMPLAN_DOLLAR_REGION <- IMPLAN_DOLLAR %>% filter(Impact %in% c('Income','Output'
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########################Plot of total impact in US and in Wyoming
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IMPLAN_REGION_DOLLAR_PLOT <- ggplot(IMPLAN_DOLLAR_REGION ,aes(x=Year,y=value/10^9,fill=Region,group=Region))+geom_area()+facet_wrap(~Impact,ncol=1)+ylab("Billion Dollars")+theme_bw()+ theme(plot.title = element_text(size = 22, face = "bold"), axis.title = element_text(size = 18),axis.text = element_text(size = 16),legend.text = element_text(size = 14),strip.text = element_text(size = 14),legend.position="top")+ theme(legend.title=element_blank())+scale_fill_manual(values=c("#3C3B6E","#FFC425"))+scale_x_continuous(breaks=seq(2025,2060,by=5))+scale_y_continuous(breaks=seq(0,5000,by=1))
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#IMPLAN_DOLLAR_REGION %>% group_by(Impact,Year) %>% summarize(value=sum(value)) %>% group_by(Impact) %>% summarize(Peak=max(value)/10^9)
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#IMPLAN_DOLLAR_REGION %>% filter(Year>2040) %>% group_by(Impact) %>% summarize(value=mean(value)/10^6)
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ggsave( filename = "./Results/Data Center: Dollar Values of Model.png", plot = IMPLAN_REGION_DOLLAR_PLOT, width = 8.5, height = 11*(3./4), units = "in", dpi = 300)
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########################Taxes
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IMPLAN_TAX <- IMPLAN_DOLLAR %>% filter(Impact %in% c("County","State","Federal"))
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