#Function to load IMPLAN Yearly data.
GET_IMPLAN_DATA <- function(){
	GET_FILE_US <- function(YEAR){read_csv(paste0("Model_Outputs/IMPLAN/US/US_",YEAR,"/economic_indicators_by_impact.csv")) %>% mutate(Year=YEAR) %>% filter(!is.na(Impact))%>% mutate(Region="US") }
	GET_FILE_WY <- function(YEAR){read_csv(paste0("Model_Outputs/IMPLAN/Wyoming/WY_",YEAR,"/economic_indicators_by_impact.csv")) %>% mutate(Year=YEAR) %>% filter(!is.na(Impact))%>% mutate(Region="WY") }
DATA <-rbind(lapply(2028:2036,GET_FILE_US) %>% bind_rows()%>% rename(Income=`Labor Income`)  %>% mutate(Income=parse_number(Income),`Value Added`=parse_number(`Value Added`),Output=parse_number(Output)) ,
lapply(2028:2036,GET_FILE_WY) %>% bind_rows()%>% rename(Income=`Labor Income`)  %>% mutate(Income=parse_number(Income),`Value Added`=parse_number(`Value Added`),Output=parse_number(Output)))

	DATA$Impact <- gsub("3 - ","",gsub("2 - ","",gsub("1 - ","",DATA$Impact)))
	DATA <-  DATA %>% pivot_longer(-c(Impact,Year,Region)) %>% rename(Type=Impact,Impact=name)
	DATA$Impact <- gsub("3 - ","",gsub("2 - ","",gsub("1 - ","",DATA$Impact)))
	DATA <- DATA %>% mutate(Source='IMPLAN') %>% select(Type,Year,Region,Impact,Source,value)
	######Append
	TEMP <- DATA %>% filter(Year==2036)
	RES <- TEMP %>% mutate(Year=2037)
	for(i in 2038:2060){
		RES <- RES %>% rbind(TEMP %>% mutate(Year=i))
	}
	DATA <- DATA %>% full_join(RES) %>% unique

return(DATA)
}