{
  "arguments": {
    "data": {
      "type_value": "Array"
    },
    "lower": {
      "type_value": "Array",
      "default_python": "None",
      "default_rust": "None",
      "description": "Estimated minimum possible value of the statistic. Only useful for the snapping mechanism. Atomic data type must be float."
    },
    "upper": {
      "type_value": "Array",
      "default_python": "None",
      "default_rust": "None",
      "description": "Estimated maximum possible value of the statistic. Only useful for the snapping mechanism. Atomic data type must be float."
    }
  },
  "id": "DPVariance",
  "name": "dp_variance",
  "options": {
    "mechanism": {
      "type_proto": "string",
      "type_rust": "String",
      "default_python": "\"Automatic\"",
      "default_rust": "String::from(\"Automatic\")",
      "description": "Privatizing mechanism to use. Value must be one of [`Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]."
    },
    "privacy_usage": {
      "type_proto": "repeated PrivacyUsage",
      "type_rust": "Vec<proto::PrivacyUsage>",
      "default_python": "None",
      "description": "Object describing the type and amount of privacy to be used for the mechanism release. Atomic data type value must be float. Example value: {'epsilon': 0.5}"
    },
    "finite_sample_correction": {
      "type_proto": "bool",
      "type_rust": "bool",
      "default_python": "True",
      "default_rust": "true",
      "description": "Whether or not to use the finite sample correction (Bessel's correction)."
    }
  },
  "return": {
    "type_value": "Array",
    "description": "Differentially private sample variance for each column of the data."
  },
  "description": "Returns a differentially private estimate of the variance for each column of the data.",
  "proto_id": 18
}