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Modified on: Mon, Jul 15, 2019 at 4:37 PM

Organize information into buckets to analyze data between categories, or set and evaluate conditions to analyze data between categories.



Where can I get more information on categorization functions?
For a list of categorization functions see the Function Reference guide.
Bucketing and conditional functions are both categorization functions. What’s the difference?
With bucketing functions, you categorize data by defining ranges. The platform evaluates the data and assigns it to the appropriate range. With conditional functions, you categorize data by defining conditions. The platform evaluates the data and accepts or rejects it into the category.
How do I determine the list of ranges for bucketing functions?
Based on your data, determine the start and end values of the range, then the length of the intervals. For example, the list 0, 25, 50, 75, 100 has a start value of 0, an end value of 100, and an interval of 25. From this list, DSCVR creates five “buckets” and categorizes the data in the following way.

List valueRange
0< = 0
251 - 25
5026 - 50
7551 - 75
100> 100

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