Ungroups the data dictionary element(s). This function ungroups both the 'Variables' and 'Categories' elements (if both are grouped data frames). This function is analogous to running dplyr::ungroup(). data_dict_group_by() allows to group a data dictionary and this function reverses the effect.

data_dict_ungroup(data_dict)

Arguments

data_dict

A list of data frame(s) representing metadata to be transformed.

Value

A list of data frame(s) identifying a workable data dictionary structure.

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.

Examples

{

library(dplyr)

# use madshapR_examples provided by the package
# Create a list of data dictionaries where the column 'table' is added to 
# refer to the associated dataset. The object created is not a 
# data dictionary per say, but can be used as a structure which can be 
# shaped into a data dictionary.

data_dict_list <- list(
  data_dict_1 = madshapR_examples$`data_dictionary_example` ,
  data_dict_2 = madshapR_examples$`data_dictionary_example`)

data_dict_nest <-
  data_dict_list_nest(data_dict_list, name_group = "table") %>%
  data_dict_group_by(col = "table")

glimpse(data_dict_ungroup(data_dict_nest))

}
#> List of 2
#>  $ Variables : tibble [18 × 9] (S3: tbl_df/tbl/data.frame)
#>   ..$ table                : chr [1:18] "data_dict_1" "data_dict_1" "data_dict_1" "data_dict_1" ...
#>   ..$ index                : chr [1:18] "1" "2" "3" "4" ...
#>   ..$ name                 : chr [1:18] "part_id" "gndr" "height" "weight_ms" ...
#>   ..$ label:en             : chr [1:18] "id of the participant" "gndr" "height" "weight_ms" ...
#>   ..$ description:en       : chr [1:18] "id of the participant" "gender of the participant" "height of the participant" "weight of the participant - measured" ...
#>   ..$ valueType            : chr [1:18] "text" "integer" "integer" "integer" ...
#>   ..$ unit                 : chr [1:18] NA NA "cm" "kg" ...
#>   ..$ datacollection::type : chr [1:18] "automatic" "declared" "declared" "measured" ...
#>   ..$ datacollection::level: chr [1:18] "high" "high" "moderate" "moderate" ...
#>  $ Categories: tibble [22 × 5] (S3: tbl_df/tbl/data.frame)
#>   ..$ table   : chr [1:22] "data_dict_1" "data_dict_1" "data_dict_1" "data_dict_1" ...
#>   ..$ variable: chr [1:22] "gndr" "gndr" "gndr" "weight_ms" ...
#>   ..$ name    : chr [1:22] "1" "2" "-77" "-88" ...
#>   ..$ label:en: chr [1:22] "Male" "Female" "Don’t want to answer" "Don’t want to answer" ...
#>   ..$ missing : chr [1:22] "FALSE" "FALSE" "TRUE" "TRUE" ...