digits <- as.character ( c("0", seq(1:9)) )
prod_na_construct <- read.csv("not_included/prod_na_construct.csv", stringsAsFactors = F)
names (prod_na_construct) <- c("part_1", "code_1")
prod_na_q2 <- prod_na_construct %>%
filter ( code_1 > 32)
prod_na_q1 <- prod_na_construct %>%
filter ( code_1 < 33) %>%
dplyr::rename( code_2 = code_1) %>%
dplyr::rename ( part_3 = part_1)
prod_na_vocabulary <- readxl::read_excel(path = "not_included/prod_na.xlsx")
names (prod_na_vocabulary ) <- gsub( ":", "_", names (prod_na_vocabulary ))
prod_na_code <- prod_na_vocabulary %>%
select ( ns4_notation3, ns4_prefLabel ) %>%
mutate ( part_1 = ns4_notation3) %>%
left_join ( ., prod_na_q2) %>%
mutate ( part_2 = ifelse ( is.na(code_1),ns4_notation3, NA )) %>%
mutate ( part_2 = ifelse ( stringr::str_sub( part_2, 1,4) == "CPA_",
yes = stringr::str_sub( part_2, 5, -1),
no = part_2)) %>%
mutate ( part_3 = ifelse ( is.na(code_1),
yes = stringr::str_sub( part_2, 1,1),
no = NA )) %>%
left_join ( ., prod_na_q1 ) %>%
mutate ( temp_code = ifelse ( nchar(part_2)>=3,
yes = stringr::str_sub( part_2, 2,3),
no = part_2)) %>%
mutate ( digit_3 = ifelse ( stringr::str_sub(temp_code, 1,1) %in% digits,
stringr::str_sub(temp_code, 1,1), "0")) %>%
mutate ( digit_4 = ifelse ( stringr::str_sub(temp_code, 2,2) %in% digits,
stringr::str_sub(temp_code, 2,2), "0")) %>%
mutate ( code_2 = ifelse ( !is.na(code_1), code_1, code_2 )) %>%
mutate ( ordering_r = as.numeric(paste0(code_2, digit_3, digit_4)))
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