This tries to find a column name in a data set based on information from the antibiotics data set. Also supports WHONET abbreviations.
guess_ab_col(x = NULL, search_string = NULL, verbose = FALSE)
Arguments
| x | |
|---|---|
| search_string | a text to search |
| verbose | a logical to indicate whether additional info should be printed |
Value
A column name of x, or NULL when no result is found.
Details
You can look for an antibiotic (trade) name or abbreviation and it will search x and the antibiotics data set for any column containing a name or code of that antibiotic. Longer columns names take precendence over shorter column names.
Stable lifecycle
The lifecycle of this function is stable. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
If the unlying code needs breaking changes, they will occur gradually. For example, a parameter will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
Read more on our website!
On our website https://msberends.github.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data. As we would like to better understand the backgrounds and needs of our users, please participate in our survey!
Examples
df <- data.frame(amox = "S", tetr = "R") guess_ab_col(df, "amoxicillin") # [1] "amox" guess_ab_col(df, "J01AA07") # ATC code of tetracycline # [1] "tetr" guess_ab_col(df, "J01AA07", verbose = TRUE) # NOTE: Using column `tetr` as input for `J01AA07` (tetracycline). # [1] "tetr" # WHONET codes df <- data.frame(AMP_ND10 = "R", AMC_ED20 = "S") guess_ab_col(df, "ampicillin") # [1] "AMP_ND10" guess_ab_col(df, "J01CR02") # [1] "AMC_ED20" guess_ab_col(df, as.ab("augmentin")) # [1] "AMC_ED20" # Longer names take precendence: df <- data.frame(AMP_ED2 = "S", AMP_ED20 = "S") guess_ab_col(df, "ampicillin") # [1] "AMP_ED20"