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Feather and Parquet files
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@ -13,7 +13,7 @@ editor_options:
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chunk_output_type: console
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---
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```{r setup, include = FALSE, results = 'markup'}
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```{r setup, include = FALSE, results = "markup"}
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knitr::opts_chunk$set(
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warning = FALSE,
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collapse = TRUE,
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@ -40,30 +40,41 @@ download_txt <- function(filename) {
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". Find more info about the structure of this data set [here](https://msberends.github.io/AMR/reference/", ifelse(filename == "antivirals", "antibiotics", filename), ".html).\n")
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github_base <- "https://github.com/msberends/AMR/raw/main/data-raw/"
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filename <- paste0("../data-raw/", filename)
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txt <- paste0(filename, ".txt")
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rds <- paste0(filename, ".rds")
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txt <- paste0(filename, ".txt")
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excel <- paste0(filename, ".xlsx")
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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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spss <- paste0(filename, ".sav")
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stata <- paste0(filename, ".dta")
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sas <- paste0(filename, ".sas")
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excel <- paste0(filename, ".xlsx")
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create_txt <- function(filename, type, software) {
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paste0("* Download as [", software, " file](", github_base, filename, ") (", AMR:::formatted_filesize(filename), ") \n")
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create_txt <- function(filename, type, software, exists) {
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if (isTRUE(exists)) {
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paste0("* Download as [", software, "](", github_base, filename, ") (",
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AMR:::formatted_filesize(filename), ") \n")
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} else {
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paste0("* *(unavailable as ", software, ")*\n")
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}
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}
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if (any(file.exists(rds),
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file.exists(excel),
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file.exists(txt),
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file.exists(excel),
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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(spss),
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file.exists(stata))) {
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msg <- c(msg, "\n**Direct download links:**\n\n")
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msg <- c(msg, "\n**Direct download links:**\n\n",
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create_txt(rds, "rds", "original R Data Structure (RDS) file", file.exists(rds)),
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create_txt(txt, "txt", "tab-separated text file", file.exists(txt)),
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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(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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if (file.exists(rds)) msg <- c(msg, create_txt(rds, "rds", "R"))
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if (file.exists(excel)) msg <- c(msg, create_txt(excel, "xlsx", "Excel"))
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if (file.exists(txt)) msg <- c(msg, create_txt(txt, "txt", "plain text"))
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if (file.exists(sas)) msg <- c(msg, create_txt(sas, "sas", "SAS"))
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if (file.exists(spss)) msg <- c(msg, create_txt(spss, "sav", "SPSS"))
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if (file.exists(stata)) msg <- c(msg, create_txt(stata, "dta", "Stata"))
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paste0(msg, collapse = "")
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}
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@ -87,14 +98,13 @@ print_df <- function(x, rows = 6) {
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}) %>%
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knitr::kable(align = "c")
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}
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```
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All reference data (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this `AMR` package are reliable, up-to-date and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply tab separated files that are machine-readable and suitable for input in any software program, such as laboratory information systems.
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All reference data (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this `AMR` package are reliable, up-to-date and freely available. We continually export our data sets to formats for use in R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated text files that are machine-readable and suitable for input in any software program, such as laboratory information systems.
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On this page, we explain how to download them and how the structure of the data sets look like.
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## Microorganisms (currently accepted names)
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## `microorganisms`: Microbial Taxonomy (currently accepted names)
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`r structure_txt(microorganisms)`
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@ -102,6 +112,8 @@ 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 Excel, 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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### Source
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Our full taxonomy of microorganisms is based on the authoritative and comprehensive:
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@ -130,7 +142,7 @@ microorganisms %>%
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print_df()
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```
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## Microorganisms (previously accepted names)
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## `microorganisms.old`: Microbial Taxonomy (previously accepted names)
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`r structure_txt(microorganisms.old)`
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@ -158,7 +170,7 @@ microorganisms.old %>%
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```
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## Antibiotic agents
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## `antibiotics`: Antibiotic Agents
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`r structure_txt(antibiotics)`
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@ -183,7 +195,7 @@ antibiotics %>%
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```
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## Antiviral agents
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## `antivirals`: Antiviral Agents
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`r structure_txt(antivirals)`
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@ -205,7 +217,7 @@ antivirals %>%
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print_df()
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```
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## Interpretation from MIC values / disk diameters to R/SI
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## `rsi_translation`: Interpretation from MIC values / disk diameters to R/SI
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`r structure_txt(rsi_translation)`
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@ -227,7 +239,7 @@ rsi_translation %>%
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```
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## Intrinsic bacterial resistance
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## `intrinsic_resistant`: Intrinsic Bacterial Resistance
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`r structure_txt(intrinsic_resistant)`
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@ -253,7 +265,7 @@ intrinsic_resistant %>%
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```
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## Dosage guidelines from EUCAST
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## `dosage`: Dosage Guidelines from EUCAST
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`r structure_txt(dosage)`
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