- Have you ever wondered what the difference is between TRUE and FALSE when creating column properties attached to property controls?
- Have you always wanted to understand what all of the transformation options do but aren’t quite sure about the menus?
- Do you want to learn more about the pivot transformation?
- Do you need to aggregate tables?
- Do you need to transform rows to columns or columns to rows?
Are you building Windows paths in Calculated Columns? Are slashes in general messing you up? Consider this workaround for using the slash character in your calculated expressions:
Let’s take this piece by piece.
- We need two slashes for a server path \\servername, but that slash happens to be an escape character. This is a problem in every programming language and it comes up because Windows paths use this particular slash. In Spotfire, you need \\\\ to escape your escape character.
- For regular folder slashes, you’ll just need two slashes for \\folder.
Finally, you’ll notice that if you try to put a slash at the end of your String, you’ll inadvertently escape your initial quotes. In Excel, this is a case for the CHAR() function, but in Spotfire we don’t deal in those data types. A workaround for this is using the NameDecode() function. This is the guidance from Spotfire Help:
Replaces all substring codes with decoded characters.
Column names in TIBCO Spotfire are stored as UTF-16 encoded strings, while variable names in TIBCO Spotfire Statistics Services are built from 8-bit ASCII characters matching [.0-9a-zA-Z] or ASCII strings enclosed in grave accents. Therefore the column names that are sent to TIBCO Spotfire Statistics Services must be encoded. Column names received from TIBCO Spotfire Statistics Services are automatically decoded by the built-in data functions output handlers. This function can be used to decode results that have not been automatically decoded.
Hope that helps, enjoy!
First, gather the people – get a team together. Find people who are onboard with your idea and are willing to put in a little extra effort to build an efficient workflow. Recruit people who understand the work processes and are willing to champion the movement towards achieving better data and better quality. For example, members on your team could include a subject matter expert, a data scientist, developer, and IT/Business Analyst.