This function joins a synonym reference table to the dataset to convert synonymous data to a unified naming format for easier aggregation, analysis, and visualization. Users may populate the function with a dataset-specific synonym table created from TADA_GetSynonymRef and reviewed/customized by the user (recommended), or the default TADA-provided synonym table, containing suggested synonym naming for some priority characteristics. Where a suggested characteristic name, fraction, speciation, or unit is present, the function will convert the TADA.CharacteristicName, TADA.ResultSampleFractionText, and TADA.MethodSpeciationName to the target format. In cases where a target speciation differs from the existing speciation, the reference table will also apply multiplication conversion factors to the TADA.ResultMeasureValue.
Arguments
- .data
TADA dataframe
- ref
Optional argument to specify which dataframe to use as a reference file. The primary use for this argument is when a user has generated a synonym reference file unique to their data, and they made changes to that file.
- np_speciation
Boolean. Determines whether the user wants to convert nitrogen and phosphorus subspecies to speciation 'as N' and 'as P', where speciation conversions are provided. Defaults to TRUE. For example, if np_speciation is TRUE, all Nitrate with TADA.MethodSpeciationName = as NO3 will be converted to as N using molecular weight conversion factors.
Value
The input TADA dataframe with the TADA.CharacteristicName, TADA.ResultSampleFractionText, TADA.MethodSpeciationName, and TADA.ResultMeasure.MeasureUnitCode columns converted to the target values, if supplied. Also includes additional columns TADA.CharacteristicNameAssumptions, TADA.FractionAssumptions, and TADA.SpeciationAssumptions populated with additional notes about the conversion logic, and a TADA.Harmonized.Flag, indicating whether TADA columns were changed in this function.
Examples
# Load example dataset:
data(Data_6Tribes_5y)
# Create a synonym reference table for flagged, cleaned dataframe:
Data_6Tribes_5yClean <- subset(Data_6Tribes_5y, !is.na(Data_6Tribes_5y$TADA.ResultMeasureValue))
Data_6Tribes_5yClean <- TADA_FlagFraction(Data_6Tribes_5yClean, clean = TRUE)
Data_6Tribes_5yClean <- TADA_FlagResultUnit(Data_6Tribes_5yClean, clean = "invalid_only")
Data_6Tribes_5yClean <- TADA_FlagSpeciation(Data_6Tribes_5yClean, clean = "invalid_only")
Data_6Tribes_5yClean <- TADA_FlagMethod(Data_6Tribes_5yClean, clean = TRUE)
CreateRefTable <- TADA_GetSynonymRef(Data_6Tribes_5yClean)
# Append synonym reference table columns to dataframe and transform/convert
# data to the USER SUPPLIED reference table values:
Data_6Tribes_5yClean_Harmonized <- TADA_HarmonizeSynonyms(Data_6Tribes_5yClean, ref = CreateRefTable)