For each chosen column (parameter) a reference population is used to estimate n different bins. The bins are based on the quantiles of the data. Then all data is grouped by the aggregation label (e.g. well) and the data of each group is applied to the bins. The percentage of data falling into a certain bin is calculated and used to estimate a z-score. The result contains a z-score, a percentage and an absolute count for each bin of each aggregation group and each parameter. It should help to detect minor distribution changes which would not be caught with a mean or median per aggregation group of the object data.

Input ports

  1. object data Type: Data
    Table containing object based data

Output ports

  1. binned data Type: Data
    Result of the binning analysis