TopTermsExplorer
Rank the terms and n-grams of text items by count or TF-IDF.
Each item, or each value on a dataset, is one text. Count ranks terms by their total occurrences; TF-IDF ranks each term by its highest weight in any one item, which favours terms concentrated in a few items.
Parameters
- top_n : integer, default=
20 - How many terms to show, between 1 and 200.
- min_words : integer, default=
1 - Fewest words in a term: 1 for single words, 2 for pairs.
- max_words : integer, default=
2 - Most words in a term; not less than the minimum.
- score : string, default=
Count - Count ranks terms by how often they appear. TF-IDF favours terms that are frequent in a few items but rare elsewhere.
- stop_words : string, default=
English and Spanish - Common words left out, such as 'the' or 'de'.
- lowercase : boolean, default=
True - Count upper and lower case forms as the same term.
Methods
launch_exploration(self, dataset: 'DashAIDataset', explorer_info: DashAI.back.dependencies.database.models.Explorer) -> Any
TopTermsExplorerBuild a horizontal bar chart of the top terms.
Parameters
- dataset : DashAIDataset
- The selected text.
- explorer_info : Explorer
- The explorer record.
Returns
- plotly.graph_objects.Figure
- The top terms, best at the top.
rank(self, values: List[str]) -> List[tuple]
TopTermsExplorerReturn the top terms of the texts with their scores.
Parameters
- values : List[str]
- The texts.
Returns
- List[tuple]
(term, score)pairs, best first; empty when no term is left.
validate_parameters(cls, params: Dict[str, Any]) -> bool
TopTermsExplorerValidate the schema and that the term length range is ordered.
Parameters
- params : Dict[str, Any]
- The explorer parameters.
Returns
- bool
- False when the minimum words per term exceed the maximum.
get_credential(self, name: str)
ConfigObjectResolve a registered credential component by name.
Parameters
- name : str
- Credential component class name (e.g. "HuggingFaceCredential").
Returns
- BaseCredential
- An instance of the requested credential component.
get_metadata(cls) -> Dict[str, Any]
BaseExplorerGet metadata for the explorer, used by the DashAI frontend.
Returns
- Dict[str, Any]
- Dictionary containing display name, description, image preview path, category, icon, color, allowed semantic types, allowed dtypes, input cardinality constraints, and any optional capability flags declared by the explorer.
get_results(self, exploration_path: str, options: Dict[str, Any]) -> List[Any]
TextAnalysisExplorerLoad the saved figure as a plotly artifact.
Parameters
- exploration_path : str
- The file written by
save_notebook. - options : Dict[str, Any]
- Rendering options (unused).
Returns
- List[Artifact]
- One plotly artifact.
get_schema(cls) -> dict
ConfigObjectGenerates the component related Json Schema.
Returns
- dict
- Dictionary representing the Json Schema of the component.
prepare_dataset(self, loaded_dataset: Any, columns: List[Dict[str, Any]]) -> Any
TextAnalysisExplorerKeep the selected column and the item columns a document provides.
Parameters
- loaded_dataset : DashAIDataset
- The loaded explorer input.
- columns : List[Dict[str, Any]]
- The selected columns.
Returns
- DashAIDataset
- The selected columns, followed by
kind,pageandpositionwhen the input has them.
save_notebook(self, notebook_info: Any, explorer_info: Any, save_path: Any, result: Any) -> str
TextAnalysisExplorerSave the plotly figure of the exploration as JSON.
Parameters
- notebook_info : Notebook
- The notebook record (unused).
- explorer_info : Explorer
- The explorer record, whose id names the file.
- save_path : Path
- The directory to save into.
- result : plotly.graph_objects.Figure
- The figure from
launch_exploration.
Returns
- str
- The saved file path as a POSIX string.
set_context(self, context: Dict[str, Any]) -> None
BaseExplorerSet optional runtime context for explorers that need extra inputs.
text_column(dataset: Any, explorer_info: Any) -> List[str]
TextAnalysisExplorerReturn the selected text values, with missing values as empty text.
Parameters
- dataset : DashAIDataset
- The prepared dataset.
- explorer_info : Explorer
- The explorer record naming the selected column.
Returns
- List[str]
- The values of the first selected column.
validate_and_transform(self, raw_data: dict) -> dict
ConfigObjectIt takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.
Parameters
- raw_data : dict
- A dictionary with the data provided by the user to initialize the model.
Returns
- dict
- A validated dictionary with the necessary objects.
validate_columns(cls, explorer_info: DashAI.back.dependencies.database.models.Explorer, column_spec: Dict[str, Dict[str, str]]) -> bool
BaseExplorerValidate that the selected columns satisfy the explorer's constraints.
Parameters
- explorer_info : Explorer
- The database record for the explorer instance, including the selected columns.
- column_spec : Dict[str, Dict[str, str]]
- A mapping from column name to a dict with at least
"type"(semantic type name) and"dtype"(dtype string).
Returns
- bool
- True if all column constraints are satisfied, False otherwise.