{
  "slug": "pandasai",
  "name": "PandasAI",
  "company": "PandasAI",
  "website": "https://docs.pandas-ai.com/",
  "category": "data-analytics",
  "business_model": "open",
  "availability": "unknown",
  "launched": null,
  "tags": [
    "sql",
    "developer-tools"
  ],
  "updated": "2026-11-03",
  "sources": [
    {
      "title": "PandasAI — official product",
      "url": "https://docs.pandas-ai.com/"
    },
    {
      "title": "PandasAI — official documentation and terms",
      "url": "https://github.com/sinaptik-ai/pandas-ai"
    }
  ],
  "selection": {
    "tasks": [
      "data-analysis"
    ],
    "form_factor": "library",
    "platforms": [
      "unknown"
    ],
    "deployment": [
      "unknown"
    ],
    "offline": "unknown",
    "regions": [
      "unknown"
    ],
    "api": "unknown",
    "license": "unknown",
    "commercial_use": "unknown",
    "languages": [
      "unknown"
    ],
    "billing": {
      "models": [
        "open-source",
        "enterprise-quote"
      ],
      "free_allowance": "yes",
      "requires_subscription": "no"
    }
  },
  "selection_evidence": {
    "tasks": {
      "status": "editorial_inference",
      "note": "Editorial classification of the documented features; not a product-performance test."
    },
    "form_factor": {
      "status": "editorial_inference",
      "note": "Editorial classification of the documented features; not a product-performance test."
    },
    "platforms": {
      "status": "unknown",
      "note": "This product-specific field was not established in this entry’s source review."
    },
    "deployment": {
      "status": "unknown",
      "note": "This product-specific field was not established in this entry’s source review."
    },
    "offline": {
      "status": "unknown",
      "note": "This product-specific field was not established in this entry’s source review."
    },
    "regions": {
      "status": "unknown",
      "note": "This product-specific field was not established in this entry’s source review."
    },
    "api": {
      "status": "unknown",
      "note": "This product-specific field was not established in this entry’s source review."
    },
    "license": {
      "status": "unknown",
      "note": "This product-specific field was not established in this entry’s source review."
    },
    "commercial_use": {
      "status": "unknown",
      "note": "This product-specific field was not established in this entry’s source review."
    },
    "languages": {
      "status": "unknown",
      "note": "This product-specific field was not established in this entry’s source review."
    },
    "billing": {
      "status": "editorial_inference",
      "note": "Editorial classification of the documented features; not a product-performance test."
    }
  },
  "facts": [
    {
      "id": "pandasai.capability.primary",
      "field": "capability",
      "value": "Ask questions over dataframes and connected databases",
      "status": "verified",
      "evidence_type": "official_page",
      "checked": "2026-11-03",
      "sources": [
        "https://docs.pandas-ai.com/"
      ]
    }
  ],
  "docs_url": "https://docs.pandas-ai.com/",
  "description": "Python library that translates natural-language data questions into executable Python or SQL.",
  "overview": "Typical uses include Natural-language data exploration; Analysis of connected business datasets. Documented capabilities: Ask questions over dataframes and connected databases; Generate charts and visual data summaries; Run generated analysis code in an optional Docker sandbox.",
  "features": [
    "Ask questions over dataframes and connected databases",
    "Generate charts and visual data summaries",
    "Run generated analysis code in an optional Docker sandbox"
  ],
  "use_cases": [
    "Natural-language data exploration",
    "Analysis of connected business datasets"
  ],
  "pricing_notes": "The core library uses the MIT expat license, while the pandasai/ee directory has separate enterprise terms. Model API calls and code-execution infrastructure cost separately; an open core does not include a free enterprise license or hosted model allowance.",
  "faq": [
    {
      "q": "Where does PandasAI fit in a workflow?",
      "a": "Python library that translates natural-language data questions into executable Python or SQL. Ask questions over dataframes and connected databases."
    },
    {
      "q": "What costs and limits should I compare before choosing PandasAI?",
      "a": "The core library uses the MIT expat license, while the pandasai/ee directory has separate enterprise terms. Model API calls and code-execution infrastructure cost separately; an open core does not include a free enterprise license or hosted model allowance."
    }
  ],
  "i18n": {
    "zh": {
      "description": "将自然语言数据问题转为可执行Python或SQL的Python库。",
      "overview": "典型用途包括自然语言数据探索、已连接业务数据集分析。文档列明的能力包括：对数据框和连接数据库提问；生成图表及可视化数据摘要；在可选Docker沙箱运行生成分析代码。",
      "features": [
        "对数据框和连接数据库提问",
        "生成图表及可视化数据摘要",
        "在可选Docker沙箱运行生成分析代码"
      ],
      "use_cases": [
        "自然语言数据探索",
        "已连接业务数据集分析"
      ],
      "pricing_notes": "核心库采用MIT expat许可，pandasai/ee目录有独立企业条款。模型API调用及代码执行基础设施另计，开放核心不附送企业许可或托管模型额度。",
      "faq": [
        {
          "q": "PandasAI适合工作流中的哪个环节？",
          "a": "将自然语言数据问题转为可执行Python或SQL的Python库。 对数据框和连接数据库提问."
        },
        {
          "q": "选择PandasAI前应比较哪些费用和限制？",
          "a": "核心库采用MIT expat许可，pandasai/ee目录有独立企业条款。模型API调用及代码执行基础设施另计，开放核心不附送企业许可或托管模型额度。"
        }
      ],
      "selection_evidence": {
        "tasks": {
          "note": "依据所记录功能作出的编辑归类，非产品性能实测。"
        },
        "form_factor": {
          "note": "依据所记录功能作出的编辑归类，非产品性能实测。"
        },
        "platforms": {
          "note": "本条目的来源核查尚未确认这一产品字段。"
        },
        "deployment": {
          "note": "本条目的来源核查尚未确认这一产品字段。"
        },
        "offline": {
          "note": "本条目的来源核查尚未确认这一产品字段。"
        },
        "regions": {
          "note": "本条目的来源核查尚未确认这一产品字段。"
        },
        "api": {
          "note": "本条目的来源核查尚未确认这一产品字段。"
        },
        "license": {
          "note": "本条目的来源核查尚未确认这一产品字段。"
        },
        "commercial_use": {
          "note": "本条目的来源核查尚未确认这一产品字段。"
        },
        "languages": {
          "note": "本条目的来源核查尚未确认这一产品字段。"
        },
        "billing": {
          "note": "依据所记录功能作出的编辑归类，非产品性能实测。"
        }
      },
      "facts": {
        "pandasai.capability.primary": {
          "value": "对数据框和连接数据库提问"
        }
      }
    },
    "es": {
      "description": "Biblioteca Python que traduce preguntas de datos a Python o SQL ejecutable.",
      "overview": "Usos habituales: Exploración de datos en lenguaje natural; Análisis de datos empresariales conectados. Funciones documentadas: Preguntas sobre dataframes y bases conectadas; Gráficos y resúmenes visuales; Código de análisis en sandbox Docker opcional.",
      "features": [
        "Preguntas sobre dataframes y bases conectadas",
        "Gráficos y resúmenes visuales",
        "Código de análisis en sandbox Docker opcional"
      ],
      "use_cases": [
        "Exploración de datos en lenguaje natural",
        "Análisis de datos empresariales conectados"
      ],
      "pricing_notes": "La biblioteca central usa MIT expat, mientras pandasai/ee tiene términos empresariales separados. Modelos e infraestructura de ejecución cuestan aparte; el núcleo abierto no incluye licencia empresarial ni cuota alojada.",
      "faq": [
        {
          "q": "¿En qué parte del flujo encaja PandasAI?",
          "a": "Biblioteca Python que traduce preguntas de datos a Python o SQL ejecutable. Preguntas sobre dataframes y bases conectadas."
        },
        {
          "q": "¿Qué costes y límites debo comparar antes de elegir PandasAI?",
          "a": "La biblioteca central usa MIT expat, mientras pandasai/ee tiene términos empresariales separados. Modelos e infraestructura de ejecución cuestan aparte; el núcleo abierto no incluye licencia empresarial ni cuota alojada."
        }
      ],
      "selection_evidence": {
        "tasks": {
          "note": "Clasificación editorial de las funciones documentadas; no es una prueba de rendimiento."
        },
        "form_factor": {
          "note": "Clasificación editorial de las funciones documentadas; no es una prueba de rendimiento."
        },
        "platforms": {
          "note": "La revisión de fuentes de esta entrada no estableció este dato del producto."
        },
        "deployment": {
          "note": "La revisión de fuentes de esta entrada no estableció este dato del producto."
        },
        "offline": {
          "note": "La revisión de fuentes de esta entrada no estableció este dato del producto."
        },
        "regions": {
          "note": "La revisión de fuentes de esta entrada no estableció este dato del producto."
        },
        "api": {
          "note": "La revisión de fuentes de esta entrada no estableció este dato del producto."
        },
        "license": {
          "note": "La revisión de fuentes de esta entrada no estableció este dato del producto."
        },
        "commercial_use": {
          "note": "La revisión de fuentes de esta entrada no estableció este dato del producto."
        },
        "languages": {
          "note": "La revisión de fuentes de esta entrada no estableció este dato del producto."
        },
        "billing": {
          "note": "Clasificación editorial de las funciones documentadas; no es una prueba de rendimiento."
        }
      },
      "facts": {
        "pandasai.capability.primary": {
          "value": "Preguntas sobre dataframes y bases conectadas"
        }
      }
    },
    "fr": {
      "description": "Bibliothèque Python traduisant les questions sur les données en Python ou SQL exécutable.",
      "overview": "Usages courants : Exploration des données en langage naturel; Analyse des données métier connectées. Fonctions documentées : Questions sur dataframes et bases connectées; Graphiques et résumés visuels; Code d’analyse dans un bac Docker facultatif.",
      "features": [
        "Questions sur dataframes et bases connectées",
        "Graphiques et résumés visuels",
        "Code d’analyse dans un bac Docker facultatif"
      ],
      "use_cases": [
        "Exploration des données en langage naturel",
        "Analyse des données métier connectées"
      ],
      "pricing_notes": "Le cœur utilise MIT expat, mais pandasai/ee a des conditions entreprise distinctes. Modèles et infrastructure d’exécution sont séparés ; le cœur ouvert n’inclut ni licence entreprise ni quota de modèles.",
      "faq": [
        {
          "q": "Quelle place occupe PandasAI dans un parcours de travail ?",
          "a": "Bibliothèque Python traduisant les questions sur les données en Python ou SQL exécutable. Questions sur dataframes et bases connectées."
        },
        {
          "q": "Quels coûts et limites comparer avant de choisir PandasAI ?",
          "a": "Le cœur utilise MIT expat, mais pandasai/ee a des conditions entreprise distinctes. Modèles et infrastructure d’exécution sont séparés ; le cœur ouvert n’inclut ni licence entreprise ni quota de modèles."
        }
      ],
      "selection_evidence": {
        "tasks": {
          "note": "Classement éditorial des fonctions documentées ; aucun test de performance."
        },
        "form_factor": {
          "note": "Classement éditorial des fonctions documentées ; aucun test de performance."
        },
        "platforms": {
          "note": "L’examen des sources de cette fiche n’a pas établi ce point du produit."
        },
        "deployment": {
          "note": "L’examen des sources de cette fiche n’a pas établi ce point du produit."
        },
        "offline": {
          "note": "L’examen des sources de cette fiche n’a pas établi ce point du produit."
        },
        "regions": {
          "note": "L’examen des sources de cette fiche n’a pas établi ce point du produit."
        },
        "api": {
          "note": "L’examen des sources de cette fiche n’a pas établi ce point du produit."
        },
        "license": {
          "note": "L’examen des sources de cette fiche n’a pas établi ce point du produit."
        },
        "commercial_use": {
          "note": "L’examen des sources de cette fiche n’a pas établi ce point du produit."
        },
        "languages": {
          "note": "L’examen des sources de cette fiche n’a pas établi ce point du produit."
        },
        "billing": {
          "note": "Classement éditorial des fonctions documentées ; aucun test de performance."
        }
      },
      "facts": {
        "pandasai.capability.primary": {
          "value": "Questions sur dataframes et bases connectées"
        }
      }
    },
    "ja": {
      "description": "自然言語のデータ質問を実行可能なPythonやSQLに変換するライブラリ。",
      "overview": "主な用途は自然言語によるデータ探索、接続済み業務データの分析です。資料に記載された機能：データフレームと接続DBへの質問；グラフと視覚的な要約の生成；任意のDocker環境で生成分析コードを実行。",
      "features": [
        "データフレームと接続DBへの質問",
        "グラフと視覚的な要約の生成",
        "任意のDocker環境で生成分析コードを実行"
      ],
      "use_cases": [
        "自然言語によるデータ探索",
        "接続済み業務データの分析"
      ],
      "pricing_notes": "中核ライブラリはMIT expatで、pandasai/eeは別の企業条件です。モデルAPIとコード実行基盤は別費用で、公開コアに企業ライセンスやホスト型モデル枠は含みません。",
      "faq": [
        {
          "q": "PandasAIはワークフローのどの部分に向いていますか？",
          "a": "自然言語のデータ質問を実行可能なPythonやSQLに変換するライブラリ。 データフレームと接続DBへの質問."
        },
        {
          "q": "PandasAIを選ぶ前に比較すべき費用や制限は何ですか？",
          "a": "中核ライブラリはMIT expatで、pandasai/eeは別の企業条件です。モデルAPIとコード実行基盤は別費用で、公開コアに企業ライセンスやホスト型モデル枠は含みません。"
        }
      ],
      "selection_evidence": {
        "tasks": {
          "note": "記録された機能に基づく編集上の分類であり、性能の実測ではありません。"
        },
        "form_factor": {
          "note": "記録された機能に基づく編集上の分類であり、性能の実測ではありません。"
        },
        "platforms": {
          "note": "この項目の資料確認では、この製品固有の情報は未確認です。"
        },
        "deployment": {
          "note": "この項目の資料確認では、この製品固有の情報は未確認です。"
        },
        "offline": {
          "note": "この項目の資料確認では、この製品固有の情報は未確認です。"
        },
        "regions": {
          "note": "この項目の資料確認では、この製品固有の情報は未確認です。"
        },
        "api": {
          "note": "この項目の資料確認では、この製品固有の情報は未確認です。"
        },
        "license": {
          "note": "この項目の資料確認では、この製品固有の情報は未確認です。"
        },
        "commercial_use": {
          "note": "この項目の資料確認では、この製品固有の情報は未確認です。"
        },
        "languages": {
          "note": "この項目の資料確認では、この製品固有の情報は未確認です。"
        },
        "billing": {
          "note": "記録された機能に基づく編集上の分類であり、性能の実測ではありません。"
        }
      },
      "facts": {
        "pandasai.capability.primary": {
          "value": "データフレームと接続DBへの質問"
        }
      }
    },
    "de": {
      "description": "Python-Bibliothek, die Datenfragen in ausführbares Python oder SQL übersetzt.",
      "overview": "Typische Anwendungen: Datenexploration in natürlicher Sprache; Analyse angebundener Geschäftsdaten. Dokumentierte Funktionen: Fragen an Dataframes und verbundene Datenbanken; Diagramme und visuelle Datenübersichten; Analysecode optional in Docker-Sandbox ausführen.",
      "features": [
        "Fragen an Dataframes und verbundene Datenbanken",
        "Diagramme und visuelle Datenübersichten",
        "Analysecode optional in Docker-Sandbox ausführen"
      ],
      "use_cases": [
        "Datenexploration in natürlicher Sprache",
        "Analyse angebundener Geschäftsdaten"
      ],
      "pricing_notes": "Die Kernbibliothek nutzt MIT expat, pandasai/ee hat eigene Unternehmensbedingungen. Modell-APIs und Ausführungsinfrastruktur kosten separat; der offene Kern enthält keine Enterprise-Lizenz oder Modellkontingente.",
      "faq": [
        {
          "q": "Wo passt PandasAI in den Arbeitsablauf?",
          "a": "Python-Bibliothek, die Datenfragen in ausführbares Python oder SQL übersetzt. Fragen an Dataframes und verbundene Datenbanken."
        },
        {
          "q": "Welche Kosten und Limits sollte ich vor der Wahl von PandasAI vergleichen?",
          "a": "Die Kernbibliothek nutzt MIT expat, pandasai/ee hat eigene Unternehmensbedingungen. Modell-APIs und Ausführungsinfrastruktur kosten separat; der offene Kern enthält keine Enterprise-Lizenz oder Modellkontingente."
        }
      ],
      "selection_evidence": {
        "tasks": {
          "note": "Redaktionelle Einordnung dokumentierter Funktionen; kein Leistungstest."
        },
        "form_factor": {
          "note": "Redaktionelle Einordnung dokumentierter Funktionen; kein Leistungstest."
        },
        "platforms": {
          "note": "Die Quellenprüfung dieses Eintrags hat dieses Produktfeld nicht belegt."
        },
        "deployment": {
          "note": "Die Quellenprüfung dieses Eintrags hat dieses Produktfeld nicht belegt."
        },
        "offline": {
          "note": "Die Quellenprüfung dieses Eintrags hat dieses Produktfeld nicht belegt."
        },
        "regions": {
          "note": "Die Quellenprüfung dieses Eintrags hat dieses Produktfeld nicht belegt."
        },
        "api": {
          "note": "Die Quellenprüfung dieses Eintrags hat dieses Produktfeld nicht belegt."
        },
        "license": {
          "note": "Die Quellenprüfung dieses Eintrags hat dieses Produktfeld nicht belegt."
        },
        "commercial_use": {
          "note": "Die Quellenprüfung dieses Eintrags hat dieses Produktfeld nicht belegt."
        },
        "languages": {
          "note": "Die Quellenprüfung dieses Eintrags hat dieses Produktfeld nicht belegt."
        },
        "billing": {
          "note": "Redaktionelle Einordnung dokumentierter Funktionen; kein Leistungstest."
        }
      },
      "facts": {
        "pandasai.capability.primary": {
          "value": "Fragen an Dataframes und verbundene Datenbanken"
        }
      }
    },
    "pt": {
      "description": "Biblioteca Python que traduz perguntas em Python ou SQL executável.",
      "overview": "Usos comuns: Exploração de dados em linguagem natural; Análise de dados empresariais conectados. Recursos documentados: Perguntas sobre dataframes e bancos conectados; Gráficos e resumos visuais; Código de análise em sandbox Docker opcional.",
      "features": [
        "Perguntas sobre dataframes e bancos conectados",
        "Gráficos e resumos visuais",
        "Código de análise em sandbox Docker opcional"
      ],
      "use_cases": [
        "Exploração de dados em linguagem natural",
        "Análise de dados empresariais conectados"
      ],
      "pricing_notes": "A biblioteca central usa MIT expat, mas pandasai/ee tem termos empresariais separados. Modelos e infraestrutura de execução custam à parte; o núcleo aberto não inclui licença empresarial nem franquia hospedada.",
      "faq": [
        {
          "q": "Em que parte do fluxo PandasAI se encaixa?",
          "a": "Biblioteca Python que traduz perguntas em Python ou SQL executável. Perguntas sobre dataframes e bancos conectados."
        },
        {
          "q": "Quais custos e limites comparar antes de escolher PandasAI?",
          "a": "A biblioteca central usa MIT expat, mas pandasai/ee tem termos empresariais separados. Modelos e infraestrutura de execução custam à parte; o núcleo aberto não inclui licença empresarial nem franquia hospedada."
        }
      ],
      "selection_evidence": {
        "tasks": {
          "note": "Classificação editorial dos recursos documentados; não é um teste de desempenho."
        },
        "form_factor": {
          "note": "Classificação editorial dos recursos documentados; não é um teste de desempenho."
        },
        "platforms": {
          "note": "A revisão de fontes desta entrada não estabeleceu este dado do produto."
        },
        "deployment": {
          "note": "A revisão de fontes desta entrada não estabeleceu este dado do produto."
        },
        "offline": {
          "note": "A revisão de fontes desta entrada não estabeleceu este dado do produto."
        },
        "regions": {
          "note": "A revisão de fontes desta entrada não estabeleceu este dado do produto."
        },
        "api": {
          "note": "A revisão de fontes desta entrada não estabeleceu este dado do produto."
        },
        "license": {
          "note": "A revisão de fontes desta entrada não estabeleceu este dado do produto."
        },
        "commercial_use": {
          "note": "A revisão de fontes desta entrada não estabeleceu este dado do produto."
        },
        "languages": {
          "note": "A revisão de fontes desta entrada não estabeleceu este dado do produto."
        },
        "billing": {
          "note": "Classificação editorial dos recursos documentados; não é um teste de desempenho."
        }
      },
      "facts": {
        "pandasai.capability.primary": {
          "value": "Perguntas sobre dataframes e bancos conectados"
        }
      }
    },
    "ko": {
      "description": "자연어 데이터 질문을 실행 가능한 Python 또는 SQL로 바꾸는 라이브러리입니다.",
      "overview": "주요 용도는 자연어 데이터 탐색; 연결된 업무 데이터 분석입니다. 문서에 명시된 기능: 데이터프레임과 연결 DB에 질문; 차트 및 시각 데이터 요약 생성; 선택적 Docker 샌드박스에서 분석 코드 실행.",
      "features": [
        "데이터프레임과 연결 DB에 질문",
        "차트 및 시각 데이터 요약 생성",
        "선택적 Docker 샌드박스에서 분석 코드 실행"
      ],
      "use_cases": [
        "자연어 데이터 탐색",
        "연결된 업무 데이터 분석"
      ],
      "pricing_notes": "핵심 라이브러리는 MIT expat이며 pandasai/ee는 별도 기업 조건입니다. 모델 API와 코드 실행 인프라 비용은 별도이고 공개 코어에 기업 라이선스나 호스팅 모델 한도는 포함되지 않습니다.",
      "faq": [
        {
          "q": "PandasAI은(는) 워크플로의 어느 단계에 적합한가요?",
          "a": "자연어 데이터 질문을 실행 가능한 Python 또는 SQL로 바꾸는 라이브러리입니다. 데이터프레임과 연결 DB에 질문."
        },
        {
          "q": "PandasAI 선택 전에 어떤 비용과 제한을 비교해야 하나요?",
          "a": "핵심 라이브러리는 MIT expat이며 pandasai/ee는 별도 기업 조건입니다. 모델 API와 코드 실행 인프라 비용은 별도이고 공개 코어에 기업 라이선스나 호스팅 모델 한도는 포함되지 않습니다."
        }
      ],
      "selection_evidence": {
        "tasks": {
          "note": "문서화된 기능에 따른 편집상 분류이며 성능 실측이 아닙니다."
        },
        "form_factor": {
          "note": "문서화된 기능에 따른 편집상 분류이며 성능 실측이 아닙니다."
        },
        "platforms": {
          "note": "이 항목의 출처 검토에서 해당 제품 정보를 확인하지 못했습니다."
        },
        "deployment": {
          "note": "이 항목의 출처 검토에서 해당 제품 정보를 확인하지 못했습니다."
        },
        "offline": {
          "note": "이 항목의 출처 검토에서 해당 제품 정보를 확인하지 못했습니다."
        },
        "regions": {
          "note": "이 항목의 출처 검토에서 해당 제품 정보를 확인하지 못했습니다."
        },
        "api": {
          "note": "이 항목의 출처 검토에서 해당 제품 정보를 확인하지 못했습니다."
        },
        "license": {
          "note": "이 항목의 출처 검토에서 해당 제품 정보를 확인하지 못했습니다."
        },
        "commercial_use": {
          "note": "이 항목의 출처 검토에서 해당 제품 정보를 확인하지 못했습니다."
        },
        "languages": {
          "note": "이 항목의 출처 검토에서 해당 제품 정보를 확인하지 못했습니다."
        },
        "billing": {
          "note": "문서화된 기능에 따른 편집상 분류이며 성능 실측이 아닙니다."
        }
      },
      "facts": {
        "pandasai.capability.primary": {
          "value": "데이터프레임과 연결 DB에 질문"
        }
      }
    }
  },
  "verification": {
    "last_checked": "2026-11-03",
    "batch": "catalog-500-20261103",
    "source_review": "Official product pages read; no product-performance test.",
    "reviewed_sources": [
      "https://docs.pandas-ai.com/",
      "https://github.com/sinaptik-ai/pandas-ai"
    ],
    "egress_region": "unknown",
    "owner": "technical",
    "gap_note": "Only documented product scope and supplied claims were reviewed. Fields left unknown were not established for this entry; no launch date, geographic guarantee or licence is inferred."
  },
  "url": "https://globalaiproductindex.com/products/pandasai/"
}