When and Why to Use

Use this to let users select multiple items from each row of a grid. Best for:

• Capturing multiple associations across brands or features

• Structured multi-select input

• Attribute-based tagging questions

Supports recoding, exclusive options, and visual media rows.

Chat Style

• Rows displayed one at a time vertically, each with a set of checkboxes or buttons

• Input is grouped per row with selectable option tiles

• Specify inputs appear inline below their respective rows

Traditional Style

• Grid layout with rows and columns visible at once

• Checkbox-style inputs allow multiple selections per row

• Optimized for keyboard and remote navigation

Chat style	Traditional with Images	Traditional - Mobile optimized

Configuration Options

Option	Type	Required	Default	Description
question	string	yes	-	The prompt shown to the user
rows	`List[str	MediaItem]`	yes	-
row_name	string	yes	-	Label used in reporting and data schema
options	`List[str	MediaItem]`	yes	-
style	string	no	checkbox	“checkbox” or “button” style inputs
randomize	bool	no	False	Randomize row order
randomize_options	bool	no	False	Randomize option order per row
fixed_options	List[str]	no	-	Options not affected by randomization
exclusive_options	List[str]	no	-	Options that deselect others in same row
specify_option	str	no	-	Adds an “Other” input to each row
specify_text	str	no	“Please specify”	Prompt shown when specifying input
image	MediaItem	no	-	Top-level image shown above the question
recodes	Dict[str, str]	no	-	Map of option values to alternate codes
default	Dict[str, List[str]]	no	random	Default selections for test data
skip_empty	bool	no	False	Skip question if no rows provided
image_label_field	str	no	-	Field to label image-based rows
show_image_label	bool	no	True	Show/hide image captions in rows
image_size	Tuple[int, int]	no	-	Size for rendering images
custom_validator	`Callable[[Dict[str, List[str]]], str	None]`	no	-
tags	s.tag()	no	-	Used in text substitution and reporting groupings

Example Code

s.grid_multi_select_question( "What do you associate with these brands? Select all that apply", row_name="Brand", rows=["Coke", "Pepsi", "Dasani", "Fanta"], options=["Tasty", "Refreshing", "Cool", "Value", "Convenient"] )

With recodes:

s.grid_multi_select_question( "What do you associate with these brands?", row_name="Brand", rows=["Coke", "Pepsi", "Fanta"], options=["Tasty", "Cool", "Value"], recodes={ "Tasty": "Product", "Cool": "Brand", "Value": "Pricing" } )

With exclusive and specify:

s.grid_multi_select_question( "Select all that apply to each option below", row_name="Item", rows=["Feature A", "Feature B"], options=["Useful", "Overused", "Unknown"], exclusive_options=["Unknown"], specify_option="Other" )

Notes

• exclusive_options allow per-row mutual exclusivity

• recodes simplify grouping similar concepts in analysis

• custom_validator lets you apply rules across the full grid

• Use randomize_options to avoid order bias