Good afternoon!
How can I build a minimum and maximum range table in quicksight, according to the example below?
Hello @jcolucci !
What does your dataset look like? Is your range based on one field or are you comparing the value of two different fields?
[quote=“duncan, post:2, topic:41013”]
What does your dataset look like? Is your range based on one field or are you comparing the value of two different fields?
Good morning!
The idea is to rank the number of users who, for example, bought with the price between zero and 10 dollars, between 11 and 20 dollars and so on and how much this represents in percentage.
I have a dimension of users and I want to count how many users bought between a metric of 10 in 10 (Y axis).
Hello @jcolucci !
Linked is a solution using a similar dataset:
Groupings by quantity
I would also recommend checking out this video:
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Hi Duncan,
Hi Duncan, good afternoon!
I used this formula to make the price ranges in quicksight but an error appears saying that custom aggregation fields are not allowed as a dimension.
How can I resolve this issue?
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Hi @jcolucci
It appears your {Unit Value Amount_USD} is using an aggregation function (SUM ?). Looking at your requirement it seems you could put your rows at the lowest level into these different brackets and your calculated field in that can be just the value at the lowest level.
Alternatively, you may need to use Level Aware Calculations to get the computations return a value at the row level.
See a similar issue resolved here.
Regards,
Giri
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Hello @jcolucci !
Were you able to try @Giridhar.Prabhu 's suggested solution above?
Hello @jcolucci, to add to @Giridhar.Prabhu’s response. Whenever I run the computation, and to create the grouping metrics, I’ll use some kind of arbitrary value to return the group values of “0-5”, “5-10”, and so on. The video does a better job of explaining this, but I’ll write a rank function that ranks all individual transactions. Then, use the maxOver function for the rank and divide it evenly to return each group value.
Then, for each group value, you can check for Unite Values that exist within them. All of these calculations require LAC-W aggregations though to avoid the calculation error.
This demo that I built in Arena goes along with the YouTube video that @duncan shared.
That should help guide you in the right direction!
Hi Dylan, good afternoon!
I think you failed to write down the step-by-step solution for me.
Could you help me with that?
Thank you!
I’m using quicksight.
Hello @jcolucci, my data is different than the data you are working with. That is why I didn’t create the exact written solution. That is why I linked the Arena analysis above that contains the steps that you will need to follow in your analysis to accomplish this. Those steps follow along with the video that was linked above as well.
I am happy to help you debug a specific error if you try implementation, but without a specific error, I am unable to assist. Thank you!