library ( dplyr) ; library (tidyr)
hr_emp <- readxl::read_excel(
path = "not_included/Croatia_labour_matching.xlsx"
) %>% select ( t_cols2, employment) %>%
filter ( !is.na(t_cols2)) %>%
mutate ( row = 1:nrow(.)) %>%
spread ( t_cols2, employment )
employment_hr <- data.frame (
code = colnames (hr_emp[, 2:ncol(hr_emp)]),
employment = as.numeric(colSums(hr_emp[, 2:ncol(hr_emp)] , na.rm = TRUE))
)
#employment_hr <- as.data.frame(t (as.matrix ( colSums(hr_emp[, 2:ncol(hr_emp)] , na.rm = TRUE))))
croatia_employment_2013 <- iotables::metadata %>%
filter ( group == "Product") %>%
filter ( variable == "t_cols") %>%
left_join ( employment_hr) %>%
select ( code, iotables_label, employment ) %>%
filter ( stats::complete.cases(.)) %>%
mutate_if (is.factor, as.character) %>%
dplyr::rename ( iotables_row = iotables_label)
devtools::use_data (croatia_employment_2013, overwrite = TRUE)
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