#' Process xlsx files from Stock SMART
#'
#' NOAA Stock SMART site https://www.st.nmfs.noaa.gov/stocksmart?app=homepage
#' hosts stock assessment data for all managed species. Data is provided iin multiple xlsx files.
#' Read in and process this data and export as tidy Rdata file
#'
#'
library(magrittr)
read_summary_files <- function(){
files <- list.files(here::here("data-raw"),pattern="\\.xlsx$") %>%
tibble::enframe(name=NULL) %>%
dplyr::rename("Files"="value")
return(files)
}
#' process summary data
#'
#'@param exportFile Boolean. To save sumamry data file as rda to data folder. (Default = T)
#'
process_stocksmart_summary_data <- function(exportFile = T){
files <- read_summary_files()
summaryfiles <- files %>% dplyr::filter(grepl("Summary",Files))
summaryData <- NULL
for (fn in unlist(summaryfiles)) {
print(fn)
dataf <- readxl::read_xlsx(here::here("data-raw",fn), col_names = T)
summaryData <- rbind(summaryData,dataf)
}
stockAssessmentSummary <- summaryData %>%
dplyr::mutate(Type = dplyr::case_when(is.na(`Update Type`) ~ `Assessment Type`,
TRUE ~ `Update Type`)) %>%
dplyr::select(-`Assessment Type`,-`Update Type`) %>%
dplyr::rename(`Assessment Type`=Type)
# remove all spaces and ? in column names
#names(stockAssessmentSummary) <- names(stockAssessmentSummary) %>%
# stringr::str_replace_all(.,"\\s+","") %>%
# stringr::str_replace(.,"\\?","") %>%
# stringr::str_replace(.,"\\/","_")
stockAssessmentSummary <- tibble::as_tibble(stockAssessmentSummary)
if (exportFile) {
usethis::use_data(stockAssessmentSummary,overwrite = T)
}
return(stockAssessmentSummary)
}
## Process Summary data
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