When and Why to Use

Use this to dynamically select a subset of items that have the fewest responses (i.e. are underrepresented) in a given quota. Ideal for:

• Ensuring even coverage across a large set of items (e.g., brands, ads, concepts)
• Avoiding over-exposure or over-sampling of frequently selected items
• Dynamically balancing stimulus presentation

This does not enforce quotas or terminate users. It simply ranks items by current counts and returns the least-filled ones.

How It Works

• Takes a list of items
• Checks which ones are least filled in the named quota
• Returns the top N least-filled items
• Often paired with multi_select_question or select_question

Configuration Options

Parameter	Type	Required	Description
number	int	yes	Number of items to return
from_list	List[Any]	yes	Full list of items to choose from
quota	str	yes	Name of the quota this list belongs to

Example Code

from survey import Survey s = Survey(**globals()) brand_list = [ 'Acura', 'Alfa Romeo', 'Aston Martin', 'Audi', 'Bentley', 'BMW', 'Bugatti', 'Buick', 'Cadillac', 'Chevrolet', 'Chrysler', 'Citroen', 'Dodge', 'Ferrari', 'Fiat', 'Ford', 'Geely', 'Genesis', 'GMC', 'Honda', 'Hyundai' # ...and so on ] brands = s.get_least_filled( number=10, from_list=brand_list, quota="Brand familiarity" ) familiar_brands = s.multi_select_question( question="Which of the following car brands have you heard of?", options=brands )

Notes

• This is often used for rotating large brand or product lists evenly
• Use set_quota() if you want to enforce a fixed distribution with termination
• Items must be trackable via the named quota so that response counts can be compared