The goal of DOPE is to provide a structured vocabulary and tools to look up details on drugs tracked by the DEA. The data structure is:
You can install the released version of DOPE from CRAN with:
install.packages("DOPE")
Run these two lines of code to install DOPE from GitHub (this requires RTools for Windows or Xcode for Mac to be installed on your computer):
if (!requireNamespace("devtools")) install.packages("devtools")
devtools::install_github("CTN-0094/DOPE")
You can look up details on a drug with the lookup()
function. It will check brand, generic and street names.
library(DOPE)
lookup("adderall")
lookup("ketamine")
lookup("auntie")
The lookup funciton supports vectorized lookups:
library(DOPE)
lookup("cheese", "pizza", "with", "a", "soda")
lookup(c("Buprenorphine", "Tramadol", "Bup/Nx"))
If your only care about the class and/or category and/or if you search returns many matches you can use the compress_lookup() function to drop columns and then remove duplicate rows.
lookup("cheese", "pizza", "with", "a", "soda") %>%
compress_lookup(compressClass = FALSE,
compressCategory = TRUE,
compressSynonym = TRUE)
DOPE now allows for parsing out drug names from a vector which contains free text with the parse()
function. You can use it in conjunction withlookup()
and compress_lookup()
data(drug_df)
parse(drug_df$textdrug[1:5]) %>%
lookup()
For more information or to see detailed vignettes, please visit https://ctn-0094.github.io/DOPE/.