text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsAmadeus ToolkitAzure Cognitive Services ToolkitCSV AgentDocument ComparisonGitHubGmail ToolkitJiraJSON AgentMultion ToolkitOffice365 ToolkitOpenAPI agentsNatural Language APIsPandas Dataframe AgentPlayWright Browser ToolkitPowerBI Dataset AgentPython AgentSpark Dataframe AgentSpark SQL AgentSQL Database AgentVectorstore AgentXorbits AgentToolsVector storesGrouped by providerIntegrationsAgent toolkitsXorbits AgentOn this pageXorbits AgentThis notebook shows how to use agents to interact with Xorbits Pandas dataframe and Xorbits Numpy ndarray. It is mostly optimized for question answering.NOTE: this agent calls the Python agent under the hood, which executes LLM generated Python code - this can be bad if the LLM generated Python code is harmful. Use cautiously.Pandas examplesâ€‹import xorbits.pandas as pdfrom langchain.agents import create_xorbits_agentfrom langchain.llms import OpenAIdata = pd.read_csv("titanic.csv")agent = create_xorbits_agent(OpenAI(temperature=0), data, verbose=True)      0%|          |   0.00/100 [00:00<?, ?it/s]agent.run("How many rows and columns are there?")            > Entering new  chain...    Thought: I need to count the number of rows and columns    Action: python_repl_ast    Action Input: data.shape    Observation: (891, 12)    Thought: I now know the final answer