knitr::opts_chunk$set(collapse = TRUE) library(REDCapExporter)
The purpose of this vignette is to show how to export a REDCap project into a R data package. Please read
vignette(topic = "api", package = "REDCapExporter")
for details on using the REDCap API to export the contents of a REDCap
project. This vignette will assume you are able to call
r qwraps2::backtick(export_core)
successfully. For the purpose of this vignette, the data set
data(avs_raw_core, package = "REDCapExporter") str(avs_raw_core)
is the result of calling
r qwraps2::backtick(export_core)
to export elements of a REDCap project containing data on the 2000-2001
Stanley Cup Champion Colorado Avalanche.
Exporting a REDCap project to a R data package is done with a call to
r paste0(qwraps2::backtick(build_r_data_package), ".")
If the reader passes the uri for the API and an API token a call to
r qwraps2::backtick(export_core)
will be made. If you prefer, or as in this case, need to have access to the
core contents of the REDCap project available, then you may pass the
r qwraps2::backtick(rcer_rccore)
object to
r qwraps2::backtick(build_r_data_package)
to build the skeleton of a R data package.
To build the skeleton of a R data package you will need to pass in the core export from the REDCap project, a path for were the source code for the data package will be written, and some some information about the users. In this context, users are the persons who have, or had, access to the REDCap project and are listed under the UserRights section of the REDCap project. The user data from REDCap is used to construct the Author section of the DESCRIPTION file for the R data package to be constructed. By default, all users are listed as 'contributors'. Modification of the roles can be provide by a named list object. In the example below, the user dewittp is going to assigned the creator and author role. To be a valid R package, at least one user will need to have the creator role assigned.
temppath <- tempdir() build_r_data_package(x = avs_raw_core, path = temppath, author_roles = list(dewittp = c("cre", "aut")))
The resulting directory is:
fs::dir_tree(temppath)
First, the package directory name. Exported packages from
r qwraps2::Rpkg(REDCapExporter)
will have the directory name rcd
The DESCRIPTION file is
prj_dir <- list.dirs(temppath) prj_dir <- prj_dir[grepl("/rcd\\d+$", prj_dir)] t(read.dcf(paste(prj_dir, "DESCRIPTION", sep = "/")))
The title comes from the project info recorded in REDCap. The version number is set as the year.month.day.hour.minute of the export. As noted above, the Author field is built from the user data stored in REDCap.
The LICENSE file notes that the package is proprietary and should not be installed or distributed to others who are not authorized to have access to the data.
cat(readLines(paste(prj_dir[1], "LICENSE", sep = "/")), sep = "\n")
The raw data exports are stored as .rds files under inst/raw-data so that these files will be available in R sessions after installing the package.
The data directory has data.table versions of the data sets.
The R/datasets.R file provides the documentation for the data sets which can be accessed in an interactive R session.
Let's install the package and explore the contents.
tar_ball <- devtools::build(pkg = prj_dir) tar_ball install.packages(pkgs = tar_ball, lib = temppath)
library(rcd14465, lib.loc = temppath)
do.call(library, args = list(package = "rcd14465", character.only = TRUE, lib.loc = temppath))
The available data sets:
data(package = "rcd14465")$results
A simple data analysis question: how many goals were scored by position?
library(data.table) as.data.table(record)[, sum(goals), by = position]
print(sessionInfo(), local = FALSE)
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