Check category dictionary — check

Checks for discrepancies between the category dictionary and column dictionary and input data.

Usage

check_categories(
  table_name = "site_info",
  inputdf = NULL,
  mytoken = getOption("drivesR.default.directustoken")
)

Arguments

table_name: The table (collection) identifier
inputdf: A data frame of prospective rows to be added to the table. If NULL, the function checks the category and column dictionaries.
mytoken: API token, formatted as "Bearer apitoken".

Value

If inputdf = NULL, it returns a data frame describing conditions and outcomes corresponding to particular tables and fields. If inputdf is provided, it returns a list with a dataframe of conditions (checkdf) and a list of categorical values in the input data that are missing from the category dictionary. This list can be used to ammend the category dictionary.

Details

First the function tests a set of preliminary conditions. Failure in any of these throws out an error message. 1) The table name is present in the column dictionary 2) The column dictionary for this table contains no category fields. 3) The table name is present in the category dictionary.

If these conditions are met, the function checks for correspondence between the category dictionary and the column dictionary. These conditions are: 1) All column_name values in the category_dictionary are specified as categories in column_dictionary. 2) No fields are missing from category_dictionary

If an input table is provided under the inputdf argument, the function checks that the contents of this table match what is in the category dictionary. The two conditions are: 1) No category columns are missing from inputdf. 2) All category levels in inputdf are present in category_dictionary.

Examples

#Not run: check_categories("site_info")