Validates the input object as a workable data dictionary structure and returns it with the appropriate madshapR::class attribute. This function mainly helps validate input within other functions of the package but could be used to check if a data dictionary is valid for use in a function.

as_data_dict_shape(object)

Arguments

object

A potential valid data dictionary to be coerced.

Value

A list of data frame(s) with madshapR::class 'data_dict_shape'.

Details

A data dictionary contains the list of variables in a dataset and metadata about the variables and can be associated with a dataset. A data dictionary object is a list of data frame(s) named 'Variables' (required) and 'Categories' (if any). To be usable in any function, the data frame 'Variables' must contain at least the name column, with all unique and non-missing entries, and the data frame 'Categories' must contain at least the variable and name columns, with unique combination of variable and name.

See also

For a better assessment, please use data_dict_evaluate().

Examples

{

library(dplyr)

# use madshapR_examples provided by the package
data_dict <- madshapR_examples$`data_dictionary_example`
data_dict <- as_data_dict_shape(data_dict)
glimpse(data_dict)

}
#> List of 2
#>  $ Variables : tibble [9 × 8] (S3: tbl_df/tbl/data.frame)
#>   ..$ index                : num [1:9] 1 2 3 4 5 6 7 8 9
#>   ..$ name                 : chr [1:9] "part_id" "gndr" "height" "weight_ms" ...
#>   ..$ label:en             : chr [1:9] "id of the participant" "gndr" "height" "weight_ms" ...
#>   ..$ description:en       : chr [1:9] "id of the participant" "gender of the participant" "height of the participant" "weight of the participant - measured" ...
#>   ..$ valueType            : chr [1:9] "text" "integer" "integer" "integer" ...
#>   ..$ unit                 : chr [1:9] NA NA "cm" "kg" ...
#>   ..$ datacollection::type : chr [1:9] "automatic" "declared" "declared" "measured" ...
#>   ..$ datacollection::level: chr [1:9] "high" "high" "moderate" "moderate" ...
#>  $ Categories: tibble [11 × 4] (S3: tbl_df/tbl/data.frame)
#>   ..$ variable: chr [1:11] "gndr" "gndr" "gndr" "weight_ms" ...
#>   ..$ name    : chr [1:11] "1" "2" "-77" "-88" ...
#>   ..$ label:en: chr [1:11] "Male" "Female" "Don’t want to answer" "Don’t want to answer" ...
#>   ..$ missing : logi [1:11] FALSE FALSE TRUE TRUE TRUE FALSE ...
#>  - attr(*, "madshapR::class")= chr "data_dict_structure"