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teal.data

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This package is used to create the data needed for teal applications. This data can be:

Independent data frames
CDISC data (for clinical trial reporting)
Relational data
MultiAssayExperiment objects

This package provides:

the mechanism for pulling data from existing systems
the ability to mutate (i.e. pre-process) the data
record the operations used to create the data to enable reproducibility

Installation

install.packages('teal.data')

Alternatively, you might want to use the development version.

# install.packages("pak")
pak::pak("insightsengineering/teal.data")

Usage

To understand how to use this package, please refer to the Introduction to teal.data article, which provides multiple examples of code implementation.

Below is the showcase of the example usage.

library(teal.data)

# quick start for clinical trial data
my_data <- cdisc_data(
  ADSL = example_cdisc_data("ADSL"),
  ADTTE = example_cdisc_data("ADTTE"),
  code = quote({
    ADSL <- example_cdisc_data("ADSL")
    ADTTE <- example_cdisc_data("ADTTE")
  })
)

# or

my_data <- within(teal_data(), {
  ADSL <- example_cdisc_data("ADSL")
  ADTTE <- example_cdisc_data("ADTTE")
})
datanames <- c("ADSL", "ADTTE")
datanames(my_data) <- datanames
join_keys(my_data) <- default_cdisc_join_keys[datanames]

# quick start for general data
my_general_data <- within(teal_data(), {
  iris <- iris
  mtcars <- mtcars
})

# reproducibility check
data <- teal_data(iris = iris, code = "iris <- mtcars")
verify(data)
#> Error: Code verification failed.
#>  Object(s) recreated with code that have different structure in data:
#>  • iris

# code extraction
iris2_data <- within(teal_data(), {iris2 <- iris[1:6, ]})
get_code(iris2_data)
#> "iris2 <- iris[1:6, ]"

Getting help

If you encounter a bug or have a feature request, please file an issue. For questions, discussions, and staying up to date, please use the teal channel in the pharmaverse slack workspace.

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