I have two tables, one containing sales per postcode and another containing sector ranges allocated to salespeople :
In my load script, I would like to add the sector to SALES table based on the range to which is linked the sales ZIP code (and country code also).
A simple join will not work for sure. So I was thinking about mapping the ZIP_2_SECTOR table to use it in the load statement of my SALES table. I don't think it will work neither.
Any tip, suggestion on the best way to go would be helpful.
Hello @patricesalem ,
You can add Country as a keyfield.
ZIP_2_SECTOR: NoConcatenate LOAD * INLINE [ZIP_START, ZIP_END, SALESPERSON, COUNTRY, SECTOR 01000, 09999, XXXX, DE, 23 10000, 25999, YYYY,DE,25]; SALES: NoConcatenate LOAD * INLINE [CUSTOMER, ZIP, COUNTRY, SECTOR, QTY_SOLD Blabla, 0500, DE, ?, 10 BliBliBli, 12500, DE,?,20 Blobloblo, 12500, NL,?,30 BluBluBlu, 12500, FR,?,5 ]; inner Join (SALES) IntervalMatch ( ZIP,COUNTRY ) LOAD ZIP_START as ZIP_START_TMP , ZIP_END as ZIP_END_TMP , COUNTRY Resident ZIP_2_SECTOR; drop table ZIP_2_SECTOR;
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I found another way to do it thanks to another post :
COMPANY: LOAD *,country as country_code; load * inline [ zip, company, country 500,Blabla,DE, 12500,BliBliBli,DE 12500,Blobloblo,NL 12500,BluBluBlu,FR ]; ZIP_2_ZONE: load * inline [ min, max, salesman, country_code 0100, 09999, TATA from DE, DE 10000, 25999, TOTO from DE,DE 10000, 25999, TATA from NL,NL 10000, 25999, TITI from FR,FR ]; Inner Join Data: IntervalMatch (zip, country_code) load num(min), num(max), country_code resident ZIP_2_ZONE; Join(COMPANY) LOAD * Resident ZIP_2_ZONE; DROP Table ZIP_2_ZONE; DROP Field country; /*
what do you think against your method ?
Hello @patricesalem ,
Glad you found the solution that works. I think it is great for the requirements you specified. I did not know all the requirements and hence this is good. It all depends which match you want to make and which fields you want to keep. You could keep the ZIP_2_ZONE table if the users also need these dimensions (to know which countries are also in the data), but from the information I got you did not need it.
Keep up the good work!