23 lines
1.4 KiB
R
23 lines
1.4 KiB
R
#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)
|
|
}
|
|
|