Creates an empty dataset using information contained in a data dictionary. The column names are taken from 'name' in the 'Variables' element of the data dictionary. If a 'valueType' or alternatively 'typeof' column is provided, the class of each column is set accordingly (default is text).
data_extract(data_dict, data_dict_apply = FALSE)A list of data frame(s) representing metadata.
Whether data dictionary(ies) should be applied to associated dataset(s), creating labelled dataset(s) with variable attributes. Any previous attributes will be preserved. FALSE by default.
A data frame identifying the dataset created from the variable names list in 'Variables' element of the data dictionary.
A dataset is a data table containing variables. A dataset object is a data frame and can be associated with a data dictionary. If no data dictionary is provided with a dataset, a minimum workable data dictionary will be generated as needed within relevant functions. Identifier variable(s) for indexing can be specified by the user. The id values must be non-missing and will be used in functions that require it. If no identifier variable is specified, indexing is handled automatically by the function.
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.
{
# use madshapR_DEMO provided by the package
data_dict <- madshapR_DEMO$data_dict_MELBOURNE
data_extract(data_dict)
}
#> # A tibble: 0 × 6
#> # ℹ 6 variables: id <chr>, Gender <int>, BMI <dbl>, age <int>,
#> # smo_status <int>, prg_curr <int>