The PARETO Procedure
- Overview
-
Getting Started
-
Syntax
-
Details
-
ExamplesCreating Before-and-After Pareto ChartsCreating Two-Way Comparative Pareto ChartsHighlighting the Vital FewHighlighting Combinations of CategoriesHighlighting Combinations of CellsOrdering Rows and Columns in a Comparative Pareto ChartMerging Columns in a Comparative Pareto ChartCreating Weighted Pareto ChartsCreating Alternative Pareto ChartsCustomizing Inset Labels and Formatting ValuesSpecifying Inset Headers and PositionsManaging a Large Number of Categories
- References
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.