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add XPT files for SAS software
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@ -50,6 +50,7 @@ download_txt <- function(filename) {
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feather <- paste0(filename, ".feather")
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parquet <- paste0(filename, ".parquet")
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sas <- paste0(filename, ".sas")
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xpt <- paste0(filename, ".xpt")
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spss <- paste0(filename, ".sav")
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stata <- paste0(filename, ".dta")
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create_txt <- function(filename, type, software, exists) {
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@ -70,6 +71,7 @@ download_txt <- function(filename) {
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file.exists(feather),
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file.exists(parquet),
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file.exists(sas),
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file.exists(xpt),
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file.exists(spss),
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file.exists(stata)
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)) {
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@ -80,7 +82,8 @@ download_txt <- function(filename) {
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create_txt(excel, "xlsx", "Microsoft Excel workbook", file.exists(excel)),
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create_txt(feather, "feather", "Apache Feather file", file.exists(feather)),
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create_txt(parquet, "parquet", "Apache Parquet file", file.exists(parquet)),
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create_txt(sas, "sas", "SAS data file", file.exists(sas)),
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create_txt(sas, "sas", "SAS data (SAS) file", file.exists(sas)),
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create_txt(xpt, "xpt", "SAS transport (XPT) file", file.exists(xpt)),
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create_txt(spss, "sav", "IBM SPSS Statistics data file", file.exists(spss)),
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create_txt(stata, "dta", "Stata DTA file", file.exists(stata))
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)
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@ -123,7 +126,7 @@ This data set is in R available as `microorganisms`, after you load the `AMR` pa
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`r download_txt("microorganisms")`
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**NOTE: The exported files for SAS, SPSS and Stata contain only the first 50 SNOMED codes per record, as their file size would otherwise exceed 100 MB; the file size limit of GitHub.** Advice? Use R instead.
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**NOTE: The exported files for SAS, SPSS and Stata contain only the first 50 SNOMED codes per record, as their file size would otherwise exceed 100 MB; the file size limit of GitHub.** Their file structures and compression techniques are very inefficient. Advice? Use R instead. It's free and much better in many ways.
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The tab-separated text file and Microsoft Excel workbook both contain all SNOMED codes as comma separated values.
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