This table contains the official used subject names.
Subject codes | Official Subjects name |
1 | public health |
2 | film studies |
3 | geographic |
4 | fashion design |
5 | acting |
6 | fine art |
The second table is the user table that has the user input subject names.
user Subject codes | user subject name |
555 | film and media |
556 | film studies |
557 | health and professional nursing |
558 | Art and Design- Fashion |
123 | Fashion and textiles |
456 | geographic Science |
3rd table
official codes | subject name |
FM888 | Film and Media |
HL999 | Health studies |
ADFj888 | Art & Design - Fashion/Textiles |
GS000 | geographic science |
AP787 | Performing arts(Acting) |
ART8077 | Fine Arts |
So my last table would be, change the user subject name to the official name, keep the user code combine with the official code.
Official codes | user code | user subject name/Official name |
FM888 | 555 | film studies |
FM888 | 556 | film studies |
HL999 | 557 | public health |
ADFj888 | 558 | fashion design |
ADFj888 | 123 | fashion design |
GS000 | 456 | geographic |
Text-mining or word matching with I have no idea what to do guys.
Solved! Go to Solution.
This gives the correct results, but would need checking and editing before extending to a larger data set. I'm excluding the words "and" and "studies", with more subjects you might also want to take out e.g. "science". There would be other options with the Alteryx Intelligence Suite but I assume you're just using Designer.
It matches words from table 1 to 2 and 2 to 3, then puts it all together to get the IDs and names you want.