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I have a large dataset of customer id's (userid) and products (marketid) which they use.
Now I'm trying to visualize relations in behaviour based on the use of a product.
For example. I can filter which customers use product 7. Now I want to see which other products they use, based on their userid.
Is their a way to organically use all user id's in marketid 7 as filter, so I can see what other products these specific users also bought? Subsequentally, I'd like to do the same for user id's in market 8, 9, 10 and so on.
@johnbeaverdam , Plot this measure with product assume customer/s are selected
measure =
var _tab = summarize(filter(all(Table), Table[customer] in allselected(Table[Customer])),Table[product])
return
calculate(coutrows(Table), filter(all(Table), Table[product] in _tab))
If want avoid all then use independent customer table
measure =
var _tab = summarize(filter((Table), Table[customer] in allselected(Customer[Customer])),Table[product])
return
calculate(coutrows(Table), filter((Table), Table[product] in _tab))
I've succesfully constructed the measure, but when I use it in visualization it shows the total number of rows.
@amitchandak wrote:@johnbeaverdam, Plot this measure with product assume customer/s are selected
What do you mean by this exactly?
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