Earn the coveted Fabric Analytics Engineer certification. 100% off your exam for a limited time only!
Hello everybody,
this is some of the raw information my report has. Would like to create a MAP to see the subtotal of sales by region for Argentina.
But Zip codes are not detected. The shipping Provinces are downloaded by letter, for example Province Buenos Aires is letter B, Ciudad Autonoma letter C, Neuquen letter Q.
How should I do to create a measure or calculated column to say if:
A = Salta
B = Buenos Aires
C = Ciudad Autonoma
...
Q = Neuquen
Z = Santa Cruz
Want to try if Power BI detects Argentinian provinces. But would prefer to detect by ZIP for more precision. Any ideas?
Thanks & Regards
Solved! Go to Solution.
You can create a new DAX Column using SWITCH like this... Just add all other letters and their corresponding values
Column = SWITCH ( 'Table Name'[Province], "A", "Salta", "B", "Buenos Aires", "C", "Ciudad Autonoma", "Q", "Neuquen" )
Or in the Query Editor - Add column tab - Conditional Column
Hope this helps!
Try plotting the Provinces' names with ArcGIS - seems to work there
I can see they don't plot all correctly in PBI
I suspect some of those Province names may have to be adjusted to plot correctly in the native PBI maps
Look at my response here (similar but in Spain)
Thanks Sean,
About using the provinces, i need to create a new column with them, the ones i have in my report are letters..
A = Salta,
B = Buenos Aires
C = Ciudad Autonoma
...
Q = Neuquen...
would you please help me, with the formula to create the new calculated column to transform each letter in a State/Province?
Thanks!
You can create a new DAX Column using SWITCH like this... Just add all other letters and their corresponding values
Column = SWITCH ( 'Table Name'[Province], "A", "Salta", "B", "Buenos Aires", "C", "Ciudad Autonoma", "Q", "Neuquen" )
Or in the Query Editor - Add column tab - Conditional Column
Hope this helps!
User | Count |
---|---|
128 | |
108 | |
99 | |
65 | |
62 |
User | Count |
---|---|
137 | |
115 | |
102 | |
71 | |
61 |