| check_dataset_variables {madshapR} | R Documentation |
Assess a data dictionary and associated dataset for undeclared variables
Description
Generates a data frame report of any variable that is present in a dataset but not in the associated data dictionary or present in a data dictionary but not in the associated dataset. This report can be used to help assess data structure, presence of fields, coherence across elements, and taxonomy or data dictionary formats.
Usage
check_dataset_variables(dataset, data_dict = NULL)
Arguments
dataset |
A dataset object. |
data_dict |
A list of data frame(s) representing metadata to be evaluated. |
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.
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.
Value
A data frame providing undeclared variables across a data dictionary.
Examples
{
# use madshapR_DEMO provided by the package
dataset <- madshapR_DEMO$`dataset_TOKYO - errors with data`
data_dict <- madshapR_DEMO$`data_dict_TOKYO - errors`
check_dataset_variables(dataset,data_dict)
}