Hi-sAFe has lots of variables and you might not know the name of the most interesting variable for the analysis you want to carry on. Currently, the distance matrix method to identify the variable names closest to your search sometimes returns only limited results.
You could search in which variable names the input variable_name is contained within the dataframe:
Variable names could also be grouped according to biological or physical compartments present on the scene, such as "tree", "crop" "soil". This in order to be able to see together all the variables related to one of these compartments.
Hi-sAFe has lots of variables and you might not know the name of the most interesting variable for the analysis you want to carry on. Currently, the distance matrix method to identify the variable names closest to your search sometimes returns only limited results.
You could search in which variable names the input variable_name is contained within the dataframe:
var_names <- function( dati, string_in_variableName ){ return( names( dati )[ which( grepl( string_in_variableName, names( dati ) ) ) ] ) }
Variable names could also be grouped according to biological or physical compartments present on the scene, such as "tree", "crop" "soil". This in order to be able to see together all the variables related to one of these compartments.