Details and Examples: PARETO Procedure
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Details
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Examples
Creating Before-and-After Pareto Charts Creating Two-Way Comparative Pareto Charts Highlighting the Vital Few Highlighting Combinations of Categories Highlighting Combinations of Cells Ordering Rows and Columns in a Comparative Pareto Chart Merging Columns in a Comparative Pareto Chart Creating Weighted Pareto Charts
Output Data Sets
The OUT= data set saves the information 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 within each block there is an observation. The observations are sorted in the order in which the categories are displayed on the chart. The following variables read 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
CBARS= variables
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 percent of the total count for each category. If you specify the WEIGHT= option, the variable _PCT_ saves the percent of the total weighted count.
_CMPCT_, which saves the cumulative percent for each category
See Output 13.8.2 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 displayed on the chart. If you create an OTHER= category that merges the remaining categories, an additional observation is saved with the new category. Since 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 with 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 with the OTHERNVAL= option. If you do not specify this value, an internal missing value is saved.