54 lines
2.1 KiB
R
54 lines
2.1 KiB
R
#New scripts
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GET_YEAR_DATA <- function(C_YEAR,DATA_PATH){
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DATA_PATH="./Raw_Output/Final_Output/"
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C_YEAR=2025
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FILES <- list.files(DATA_PATH)
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FILES <- paste0(DATA_PATH,FILES[grep(paste0(C_YEAR,"-"),FILES)])
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ECON_FILE <- FILES[grep("Economic",FILES)]
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TAX_FILE <- FILES[grep("Tax",FILES)]
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ECON <- read_csv(ECON_FILE)
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TAX <- read_csv(TAX_FILE)
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FILE_LIST <- list.files(paste0(DATA_PATH,C_YEAR))
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TAX_FILE <- paste0(DATA_PATH,C_YEAR,"/",FILE_LIST[grep("Taxes",FILE_LIST)])
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ECON_FILE <- paste0(DATA_PATH,C_YEAR,"/",FILE_LIST[grep("Economic",FILE_LIST)])
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DAT <- read_csv(ECON_FILE)[,-1] %>% select(-TagName)
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colnames(DAT) <- c("Event","County_Name","Impact","Employment","Labor_Income","Value_Added","Output")
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DAT <- DAT[!is.na(DAT[,1]),]
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TAX <- read_csv(TAX_FILE)[,-1] %>% select(-TagName)
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colnames(TAX) <- c("Event","County_Name","Impact","Subcounty","Special","County","State","Federal","Total")
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TAX <- TAX[!is.na(TAX[,1]),]
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TAX$STATE_TOTAL <- rowSums(TAX[,4:7])
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DAT <- full_join(DAT,TAX)
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#rm(TAX)
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DAT$County_Name <- gsub(" County, WY \\(2023\\)","",DAT$County_Name)
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DAT$Impact <- gsub(" - ","",gsub("1","",gsub("2","",gsub("3","",DAT$Impact))))
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DAT$Group <- NA
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DAT[grep('Skid',DAT$Event),"Group"] <- "Skid"
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DAT[grep('Purchase',DAT$Event),"Group"] <- "Beet Purchase"
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DAT[grep('Truck',DAT$Event),"Group"] <- "Transportation"
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DAT[DAT$Event=="Gas Production (Campbell)","Group"] <- "Gas Production"
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DAT[is.na(DAT$Group),"Group"] <- "Processing Facilities"
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#Remove the direct transportation effects induced by by beet purchases, by adding in a negative impact of rail and truck equal to the direct effect found in the first run.
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DAT[grep('Adjustment',DAT$Event),"Group"] <- "Beet Purchase"
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DAT <- DAT %>% select(Minor_Event=Event,Major_Event=Group,everything())
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DAT$Year <- C_YEAR
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DAT <-DAT %>% select(Year,everything())
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return(DAT)
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}
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GET_ALL_DATA <- function(DATA_PATH){
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YEARS_OF_DATA <- list.files(DATA_PATH)
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for(i in 1:length(YEARS_OF_DATA)){
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if(!exists("RES")){
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RES<- GET_YEAR_DATA(YEARS_OF_DATA[i],DATA_PATH)
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}else{
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RES<- rbind(RES,GET_YEAR_DATA(YEARS_OF_DATA[i],DATA_PATH)) %>% as_tibble
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}
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}
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return(RES)
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}
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