... and JMP, while we are at it. I have written several papers on Cardinality Ratio and have an sco wiki page on it. http://www.sascommunity.org/wiki/Cardinality_Ratio definitions: * the cardinality of a set is the number of elements in the set * cardinality of a data set is n-obs * cardinality of a variable is n-levels * cardinality ratio is n-levels / n-obs; * CR is a reducing function, its range is in (0:1] and it is easier to compare variable's CR than the range of n-levels in (1:n-obs) if one takes the time to calculate the n-levels of each variable proc freq data = sashelp.class nlevels; I know you have the n-obs of the data set, so, in my book it is a simple step to calculate cardinality_ratio = n-levels / n-obs; Why is this a Good Idea? Because it takes several steps to calculate it. proc contents ... out = out_contents; proc freq ... out= out_freq; proc sort out_contents proc sort out_freq data cardinality_ratio; merge out_contents out_freq; by name; cardinality_ratio = nlevels / nobs; proc summary var cardinality_ratio out = out_means data cr_type; select; when ... cr_type = 'unique'; when ... cr_type = 'many'; otherwise cr_type = 'few'; Having proc freq do the number-crunching makes calculating the cr-type in (continuous, discrete, unique) easier.
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