langchain.agents.agent_toolkits.pandas.base.create_pandas_dataframe_agent¶
langchain.agents.agent_toolkits.pandas.base.create_pandas_dataframe_agent(llm: BaseLanguageModel, df: Any, agent_type: AgentType = AgentType.ZERO_SHOT_REACT_DESCRIPTION, callback_manager: Optional[BaseCallbackManager] = None, prefix: Optional[str] = None, suffix: Optional[str] = None, input_variables: Optional[List[str]] = None, verbose: bool = False, return_intermediate_steps: bool = False, max_iterations: Optional[int] = 15, max_execution_time: Optional[float] = None, early_stopping_method: str = 'force', agent_executor_kwargs: Optional[Dict[str, Any]] = None, include_df_in_prompt: Optional[bool] = True, number_of_head_rows: int = 5, extra_tools: Sequence[BaseTool] = (), **kwargs: Dict[str, Any]) → AgentExecutor[source]¶
Construct a pandas agent from an LLM and dataframe.
Examples using create_pandas_dataframe_agent¶
Airbyte Question Answering
Pandas Dataframe
!pip install bs4