library(dplyr)
library(readxl)
# This is set up to be run from within the eesectors_data_extract folder. All
# paths are relative to that. You may need to source the utils.R script before
# running this script.
# Extract the entire worksheet from excel
tourism <- readxl::read_excel(
'../OFFICIAL/dcms/OFFICIAL_working_file_dcms_V13.xlsm',
sheet = 'Tourism',
col_names = TRUE
)
colnames(tourism) <- c('year','gva','total','perc','overlap')
# Remove the extraneous rows
tourism <- tourism %>%
dplyr::filter(!(is.na(year) & is.na(gva) & is.na(total) & is.na(perc) & is.na(overlap)))
# Save out to file
tourism %>% saveRDS('../OFFICIAL/cleaned/OFFICIAL_tourism_data.Rds')
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