Check for common data quality issues affecting modeling functions

Check the primary dataset for NAs, NaNs, Inf, and that each row is a unique choice occurrence

Usage

check_model_data(dat, project, uniqueID, latlon = NULL, save.file = TRUE)

Arguments

dat

Primary data containing information on hauls or trips. Table in FishSET database contains the string 'MainDataTable'.

project

Project name.

uniqueID

Variable in dat containing unique occurrence identifier.

latlon

Vector of names for variables with lat, lon coordinates to be check if using 'lat-lon' as starting location.

save.file

Logical, if TRUE and no data issues are identified, the dataset is saved to the FishSET database. Defaults to TRUE.

Value

Returns statements of data quality issues in the data. Saves table to FishSET database.

Details

It is best to check the data for NAs, NaNs and Inf, and that each row is a unique choice occurrence after data creation functions have been run but before making the model design file (make_model_design). These steps should be taken even if the data passed earlier data verification checks, as data quality issues can arise in the creation or modification of data. Model functions may fail or return inaccurate results if data quality issues exist. The integrated data will not save if any of these issues are in the dataset. If data passes all tests, then data will be saved in the FishSET database with the prefix ‘final’. The data index table will also be updated and saved.

Examples

if (FALSE) {
check_model_data(MainDataTable, uniqueID = "uniqueID_Code", save.file = TRUE)
}