Filter the raw mentions dataset before it is aggregated. Provide a single condition {"field","op","value"} or an {"and":[…]} / {"or":[…]} group of conditions (nest groups for mixed logic), up to 8 conditions. Operators: =, <>, <, <=, >, >=, in, not_in, like, not_like, ilike, not_ilike, match, not_match (use an array value with in / not_in). Filterable fields: ai_search_volume (monthly AI search volume); mentions (number of mentions); platform (LLM engine, e.g. chat_gpt, google); location (location name); language (language name); sources_domain (cited source domain); search_results_domain (domain in the engine's search results); brand_entities_title (brand entity title); brand_entities_category (brand entity category). Example: {"field":"ai_search_volume","op":">","value":1000}
| Name | Type | Description | Notes |
|---|---|---|---|
| var_field | str | Field to filter on. See the endpoint's list of filterable fields. | |
| op | str | Comparison operator. | |
| value | DataForSeoFilterValue | ||
| var_and | List[DataForSeoFilter] | Sub-expressions that must all match. | |
| var_or | List[DataForSeoFilter] | Sub-expressions where at least one must match. |
from unifapi.models.geo_mentions_aggregated_metrics_request_filters import GeoMentionsAggregatedMetricsRequestFilters
# TODO update the JSON string below
json = "{}"
# create an instance of GeoMentionsAggregatedMetricsRequestFilters from a JSON string
geo_mentions_aggregated_metrics_request_filters_instance = GeoMentionsAggregatedMetricsRequestFilters.from_json(json)
# print the JSON string representation of the object
print(GeoMentionsAggregatedMetricsRequestFilters.to_json())
# convert the object into a dict
geo_mentions_aggregated_metrics_request_filters_dict = geo_mentions_aggregated_metrics_request_filters_instance.to_dict()
# create an instance of GeoMentionsAggregatedMetricsRequestFilters from a dict
geo_mentions_aggregated_metrics_request_filters_from_dict = GeoMentionsAggregatedMetricsRequestFilters.from_dict(geo_mentions_aggregated_metrics_request_filters_dict)