Method get_topic

bertopic/_bertopic.py:1622–1648

Return top n words for a specific topic and their c-TF-IDF scores. Arguments: topic: A specific topic for which you want its representation full: If True, returns all different forms of topic representations for a topic, including aspects R

(self, topic: int, full: bool = False)

            return self.topic_representations_

    def get_topic(self, topic: int, full: bool = False) -> Union[Mapping[str, Tuple[str, float]], bool]:
        """Return top n words for a specific topic and their c-TF-IDF scores.

        Arguments:
            topic: A specific topic for which you want its representation
            full: If True, returns all different forms of topic representations
                  for a topic, including aspects

        Returns:
            The top n words for a specific word and its respective c-TF-IDF scores

        Examples:
        ```python
        topic = topic_model.get_topic(12)
        ```
        """
        check_is_fitted(self)
        if topic in self.topic_representations_:
            if full:
                representations = {"Main": self.topic_representations_[topic]}
                aspects = {aspect: representations[topic] for aspect, representations in self.topic_aspects_.items()}
                representations.update(aspects)
                return representations
            else:
                return self.topic_representations_[topic]
        else:
            return False

    def get_topic_info(self, topic: int | None = None) -> pd.DataFrame:
        """Get information about each topic including its ID, frequency, and name.