pandora.imputation module

pandora.imputation.impute_data(input_data: ndarray[Any, dtype[_ScalarType_co]], imputation: str | None, missing_value: float | int = nan) → ndarray[Any, dtype[_ScalarType_co]]

Imputes missing values in the given input data using the given imputation strategy.

Parameters:

input_datanpt.NDArray

Numpy array containing the input data to impute. Missing values are expected to be np.NaN.

imputationOptional[str]

Imputation method to use. Available options are:

• "mean": Imputes missing values with the average of the respective column.

• "remove": Removes all columns with at least one missing value.

• None: Does not impute the given data.

missing_valueUnion[float, int], default=np.nan

Value to treat as missing value.

Returns:

imputed_datanpt.NDArray

Imputed input data with imputation according to the specified method.

Raises:

PandoraException

• If no data is left in case of "remove" imputation strategy. That means that all columns in the input data contained at least one missing value.

• If the imputation method is not supported.