Create the filter rule — filter

This function creates the simple rule of a filter

filter_rule(
  dimension = NULL,
  metric = NULL,
  verb = NULL,
  object = NULL,
  description = NULL,
  is_distinct = FALSE,
  attribution = "repeating",
  attribution_context = "visitors",
  validate = FALSE,
  dataviewId = Sys.getenv("CJA_DATAVIEW_ID")
)

Arguments

dimension: This is the subject of the rule. The value should be the dimension id. Only the dimension or metric can be used at a time.
metric: This is the subject of the rule. The value should be the metric id. Only the dimension or metric can be used at a time.
verb: Choose from any of the 30 different verbs. Use the filter_verbs() package data to see all available verbs along with the descriptions.
object: This is the object of the rule and answers the question what or how many
description: The internal description for the rule. (optional) This will not show in the UI but could be very helpful when using the API.
is_distinct: This will filter on a distinct count of items within a dimension. Examples: “Visitors who viewed more than 5 distinct products,” or “Visits where more than 5 distinct pages were seen.”
attribution: Define the type of attribution. Either repeating (default), instance, or nonrepeating. See Details for more information.
attribution_context: When applying a non-repeating instance attribution model to a rule the context for the attribution must be visitors (default) or visits
validate: Set to TRUE when metric or dimension validation is preferred. Default is FALSE. Validation will slow down the function response time but ensure a valid rule result.
dataviewId: CJA data view id. Required if the argument validate is set to TRUE. If an environment variable called CJA_DATAVIEW_ID exists in .Renviron or elsewhere and no dataviewId argument is provided, then the CJA_DATAVIEW_ID value will be used. Use cja_get_dataviews() to get a list of available dataviewId.

Value

A structured list defining the rule for a filter

Details

Attribution Models Available for dimensions only, these models determine what values in a dimension to filter for. Dimension models are particularly useful in sequential filter.

repeating (default): Includes instances and persisted values for the dimension.
instance: Includes instances for the dimension.
nonrepeating instance: Includes unique instances (non-repeating) for the dimension. This is the model applied in Flow when repeat instances are excluded.