The OUT= data set saves the information that is displayed on a Pareto chart. If you specify CLASS= variables, the OUT= data set contains one block of observations for each combination of levels of the CLASS= variables, and each block contains an observation for each Pareto category. The observations are sorted in the order in which the categories are displayed on the chart. The following variables from a DATA= data set are saved in an OUT= data set:
process variables
CLASS= variables
BY variables
WEIGHT= variables
the CTILES= variable
the TILELEGEND= variable
the NLEGEND= variable
PBARS= variables
BARLEGEND= variables
In addition, the OUT= data set contains the following variables that are created during the analysis:
_COUNT_
, which saves the frequency count for each Pareto category
_WCOUNT_
, which saves the weighted count for each category. This variable is created only when you specify the WEIGHT=
option.
_PCT_
, which saves the percentage of the total count for each category. If you specify the WEIGHT= option, the variable _PCT_
saves the percentage of the total weighted count.
_CMPCT_
, which saves the cumulative percentage for each category
See Output 15.8.2 for an example of an OUT= data set.
If you specify the MAXNCAT= , MAXCMPCT= , or MINPCT= option, the OUT= data set saves only the categories that are displayed on the chart. If you create an OTHER= category that merges the remaining categories, an additional observation is saved with the new category. Because the OTHER= value is defined as a formatted value of the process variable, you should also specify a corresponding internal value, as follows:
If the process variable is a character variable, specify the internal value in the OTHERCVAL= option. If you do not specify this value, the OTHER= value is saved as the internal value.
If the process variable is a numeric variable, specify the internal value in the OTHERNVAL= option. If you do not specify this value, an internal missing value is saved.