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meridian.data.load.XrDatasetDataLoader

Reads data from an xarray.Dataset object.

meridian.data.load.XrDatasetDataLoader(
    dataset: xr.Dataset,
    kpi_type: str,
    name_mapping: (Mapping[str, str] | None) = None
)

  data_loader = XrDatasetDataLoader(pickle.loads('data.pickle'))
  data = data_loader.load()

Args
`dataset`	An `xarray.Dataset` object containing the input data.
`kpi_type`	A string denoting whether the KPI is of a `'revenue'` or `'non-revenue'` type. When the `kpi_type` is `'non-revenue'` and `revenue_per_kpi` exists, ROI calibration is used and the analysis is run on revenue. When `revenue_per_kpi` doesn't exist for the same `kpi_type`, custom ROI calibration is used and the analysis is run on KPI.
`name_mapping`	An optional dictionary whose keys are the current coordinates or array names in the `input` dataset and whose values are the desired coordinates (`geo`, `time`, `media_time`, `media_channel` and/or `rf_channel`, `control_variable`, `non_media_channel`, `organic_media_channel`, `organic_rf_channel`) or array names (`kpi`, `revenue_per_kpi`, `media`, `media_spend` and/or `rf_spend`, `controls`, `population`, `non_media_treatments`, `organic_media`, `organic_reach`, `organic_frequency`). Mapping must be provided if the names in the `input` dataset are different from the required ones, otherwise errors are thrown.

Attributes
`dataset`	An `xr.Dataset` object containing the input data.
`kpi_type`	A string denoting whether the KPI is of a `'revenue'` or `'non-revenue'` type. When the `kpi_type` is `'non-revenue'` and `revenue_per_kpi` exists, ROI calibration is used and the analysis is run on revenue. When `revenue_per_kpi` doesn't exist for the same `kpi_type`, custom ROI calibration is used and the analysis is run on KPI.

Methods

load() -> meridian.data.input_data.InputData

Returns an InputData object containing the data from the dataset.