At one time or another, you have likely “lost” a JMP table, journal or script. The file wasn’t really lost – just moved, altered or renamed. Traditionally, people have relied on creating a system of directories to keep track of files. There are a number of disadvantages to this method, the greatest of which is that the directory structure contains no information about what is in the files. We show a powerful and flexible file management application, built with JSL, which allows users to find data tables, journals and scripts using a variety of criteria. Topics include:
Methods for crawling through journals, scripts and data tables to extract file metadata and to categorize and locate scripts located within these files.
Combining local data filters with a hidden tabulate platform to avoid construction of complicated row selection WHERE clauses.
Using hidden output to derive and present search results.
Methods to locate and surface elements buried within large journals.
Using set operations and associative arrays to aggregate/summarize rows of multiple response columns by levels of a grouping variable.
Allowing users to view and edit file metadata without editing files directly.
WHERE clause considerations when using multiple response columns and data filters.
Published on 03-24-202509:03 AM by
Ryan_Gilmore| Updated on 03-27-202509:51 AM
Authors
Brady Brady, JMP Enablement Engineer, SAS
Donald W. McCormack, JMP Enablement Engineer, SAS
At one time or another, you have likely “lost” a JMP table, journal or script. The file wasn’t really lost – just moved, altered or renamed. Traditionally, people have relied on creating a system of directories to keep track of files. There are a number of disadvantages to this method, the greatest of which is that the directory structure contains no information about what is in the files. We show a powerful and flexible file management application, built with JSL, which allows users to find data tables, journals and scripts using a variety of criteria. Topics include:
Methods for crawling through journals, scripts and data tables to extract file metadata and to categorize and locate scripts located within these files.
Combining local data filters with a hidden tabulate platform to avoid construction of complicated row selection WHERE clauses.
Using hidden output to derive and present search results.
Methods to locate and surface elements buried within large journals.
Using set operations and associative arrays to aggregate/summarize rows of multiple response columns by levels of a grouping variable.
Allowing users to view and edit file metadata without editing files directly.
WHERE clause considerations when using multiple response columns and data filters.
